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Structure-Based Discovery of A_2A Adenosine Receptor Ligands

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† Department of Pharmaceutical Chemistry, University of California, 1700 4th Street, Box 2550, San Francisco, California 94158

‡ Molecular Recognition Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland 20892

*To whom correspondence should be addressed. For B.K.S.: phone, 415-514-4126; fax, 415-514-4260; e-mail, [email protected]. For K.A.J.: phone, 301-496-9024; fax, 301-480-8422; e-mail, [email protected]

Cite this: J. Med. Chem. 2010, 53, 9, 3748–3755

Publication Date (Web):April 20, 2010

https://doi.org/10.1021/jm100240h

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Abstract

The recent determination of X-ray structures of pharmacologically relevant GPCRs has made these targets accessible to structure-based ligand discovery. Here we explore whether novel chemotypes may be discovered for the A_2A adenosine receptor, based on complementarity to its recently determined structure. The A_2A adenosine receptor signals in the periphery and the CNS, with agonists explored as anti-inflammatory drugs and antagonists explored for neurodegenerative diseases. We used molecular docking to screen a 1.4 million compound database against the X-ray structure computationally and tested 20 high-ranking, previously unknown molecules experimentally. Of these 35% showed substantial activity with affinities between 200 nM and 9 μM. For the most potent of these new inhibitors, over 50-fold specificity was observed for the A_2A versus the related A₁ and A₃ subtypes. These high hit rates and affinities at least partly reflect the bias of commercial libraries toward GPCR-like chemotypes, an issue that we attempt to investigate quantitatively. Despite this bias, many of the most potent new ligands were novel, dissimilar from known ligands, providing new lead structures for modulation of this medically important target.

Introduction

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G-protein-coupled receptors (GPCRs^a)

Abbreviations: GPCR, G-protein-coupled receptor; AR, adenosine receptor; CNS, central nervous system; SEA, similarity ensemble approach; PDB, Protein Data Bank; WOMBAT, World of Molecular Bioactivity; CHO, Chinese hamster ovary; DMEM, Dulbecco’s modified Eagle medium; PKA, protein kinase A; DLS, dynamic light scattering.

are a large family of transmembrane proteins that signal intracellularly after binding an extracellular ligand. These receptors share a similar topology, with seven transmembrane helices, but recognize a wide range of different signaling molecules. GPCRs have been intensely studied as pharmaceutical targets, and over 40% of marketed drugs act through them. (1) Until recently, a missing link to deeper understanding of GPCRs has been a lack of atomic resolution structural information. With the recent advent of several X-ray crystal structures of pharmacologically relevant GPCRs (2-5) it has for the first time become possible to leverage high-resolution structures for ligand discovery against these targets. (6)

Among the new GPCR structures is that of the A_2A adenosine receptor (AR). (5) There are four subtypes of the AR (A₁, A_2A, A_2B, and A₃), and they are activated by extracellular adenosine in response to organ stress or tissue damage. The A_2A AR signals in both the periphery and the CNS, with agonists explored as anti-inflammatory drugs and antagonists explored for neurodegenerative diseases, e.g., Parkinson’s disease. (7-11) Although access to high resolution structural data is a crucial step toward atomic-level understanding of GPCRs, the lack of structures has certainly not been an obstacle for successful ligand discovery. For several decades, classical ligand-based medicinal chemistry approaches have been used to identify thousands of AR ligands. Almost all known AR agonists are derivatives of the cognate ligand (1−3, Chart 1), whereas antagonists are more diverse. Two large classes of AR antagonists are xanthines, with members such as caffeine (4) and theophylline (5), and adenine derivates such as 6 (ZM241385 (12)), which is bound to the A_2A AR binding site in the crystallographic structure (Chart 1, Figure 1A). Despite considerable medicinal chemistry efforts and the wide range of possible therapeutic applications for AR ligands, there are only a few approved drugs targeting this receptor. (8, 11) Consequently, there remains an ongoing need for new subtype selective agonists and antagonists of this target.

Chart 1. Structures of Known Agonists (1−3) and Antagonists (4−6) of the A_2A Adenosine Receptor

Figure 1. Binding mode of the cocrystallized ligand 6 (A) and the predicted binding modes of the seven ligands discovered in the docking screen (B−H). The A_2A AR binding site is shown in white ribbons with the side chains of Glu169 and Asn253 in sticks. In (A) the cocrystallized ligand 6 is shown using orange carbon atoms. In (B−H), the crystallographic ligand is shown using blue lines and the docking poses for the ligands are depicted with orange carbon atoms. Black dotted lines indicate hydrogen bonds. The compounds are (B) 7, (C) 8, (D) 9, (E) 10, (F) 11, (G) 12, and (H) 13.

Here, we wished to investigate whether we could find new A_2A AR ligand chemotypes by using structure-based molecular docking to screen a large and putatively unbiased library of small molecules, looking for those that complement the receptor structure. Docking evaluates the complementarity of small molecules to a receptor binding site of known structure (13-18) and can in principle discover new chemotypes, dissimilar to previous ligands, that nevertheless fit the binding site well. Such chemotypes might provide new routes for modulation of this key target. Methodologically, we wanted to explore what the hit rate of a structure-based (docking) screen against the A_2A AR might be. In docking screens against the β₂ adrenergic GPCR, a hit rate of 24% had been observed. (19-23) A docking “hit” is a molecule that binds to the target at a relevant concentration, and a docking “hit rate” is the number of compounds that bind divided by the number of compounds experimentally tested. For the β₂ adrenergic receptor, where the affinity of the best docking hit was 9 nM, both were unusually high. We wished to understand whether this would be true for this second GPCR and why this might be so. To investigate this, we docked a library of 1.4 million small molecules to the crystal structure of the A_2A AR. From the top-scoring molecules, 20 were selected on the basis of their fit to the binding site and chemical diversity. Here, we present the experimental evaluation of these molecules and assess why GPCRs appear to be particularly suitable targets for structure-based ligand discovery.

Methods

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Preparation of the Molecular Docking Screen

All docking calculations were carried out with the program DOCK 3.5.54 (16, 17, 24) using a 2.6 Å crystallographic structure of the A_2A adenosine receptor in complex with an antagonist (6) (12) (PDB accession code 3EML (5)). The receptor structure was prepared by removing all non-protein atoms and the intracellular T4-lysozyme insertion. The protonation states of ionizable residues were set to the most probable in aqueous solution at pH 7.

The flexible-ligand sampling algorithm in DOCK3.5.54 superimposes atoms of the docked molecule onto binding site matching spheres, which indicate putative ligand atom positions. (16, 17) In the case of the A_2A AR, 45 matching spheres were used, and these were either based on the atoms of the crystallographic ligand or positioned manually. The spheres were also labeled for chemical matching based on the local receptor environment. (25) The degree of ligand sampling is determined by the bin size, bin size overlap, and distance tolerance. These three parameters were set to 0.4, 0.3, and 1.5 Å, respectively, for both the binding site matching spheres and the docked molecules. For ligand conformations passing an initial steric filter, a physics-based scoring function is used to evaluate the fit to the receptor binding site. For the best scoring conformation of each docked molecule, 100 steps of rigid-body minimization are carried out. The score for each conformation is calculated as the sum of the receptor−ligand electrostatic and van der Waals interaction energy, corrected for ligand desolvation. These three terms are evaluated from precalculated grids. The three-dimensional map of the electrostatic potential in the binding site was prepared using the program Delphi. (26) In this calculation, partial charges from the united atom AMBER force field (27) were used for all receptor atoms except the side chain amide of Asn253, for which the dipole moment was increased to favor hydrogen bonding to this residue (we have adopted this technique of increasing local dipoles on a few polar residues in the active site without changing their formal charges extensively in past studies). (28, 29) The program CHEMGRID was used to generate a van der Waals grid, which is based on a united atom version of the AMBER force field. (30) The desolvation penalty for a ligand conformation is estimated from a precalculated transfer free energy of the molecule between solvents of dielectrics 78 and 2. The desolvation energy is obtained by weighting the transfer free energy with a scaling factor that reflects the degree of burial of the ligand in the receptor binding site. (31, 32)

The ZINC leadlike set was prepared by filtering a large library of commercially available compounds using the criteria log P < 3.5, molecular weight of <350, and number of rotatable bonds of ≤7. (33) Each molecule has been prepared for docking by pregenerating up to 1000 conformations using the program OMEGA. (34) Partial atomic charges and transfer free energies have been calculated using AMSOL, (35, 36) and van der Waals parameters have been derived from an all-atom AMBER potential. (37)

Similarity and Library Bias Calculations

Similarity calculations were carried out with the program Pipeline Pilot (38) using the Tanimoto coefficient and ECFP4 fingerprints. For each of the docking-discovered ligands, the Tanimoto similarity to all annotated A₁, A_2A, A_2B, and A₃ AR ligands with K_i ≤ 10 μM in the World of Molecular Bioactivity (WOMBAT 2006.2) (39) and ChEMBL (a StARlite 2009 prerelease version) (40) databases was calculated. The number of molecules in the ZINC leadlike database that are similar to known ligands of the ARs, adrenergic receptors, adenylyl cyclases, and AmpC β-lactamase was predicted with the similarity ensemble approach (SEA) using ECFP4 fingerprints. (41) Ligands (K_i ≤ 10 μM) that are annotated to ARs, adrenergic receptors, and adenylyl cyclases were extracted from the WOMBAT database. Ligands for AmpC β-lactamase were extracted from refs 28, 29, and 42. For each ligand set, the number of leadlike molecules in ZINC that have a SEA P value better than 10⁻¹⁰ was calculated. The predicted compounds were then postfiltered for molecules that match the molecular weight and formal charge ranges of the known ligands.

A_2A AR Receptor Binding and Functional Assay

Binding assays at three hAR subtypes were carried out using standard radioligands (43-45) and membrane preparations from Chinese hamster ovary (CHO) cells (A₁ and A₃) or human embryonic kidney (HEK293) cells (A_2A) stably expressing a hAR subtype. (46, 47) A functional assay at the A_2AAR consisted of stimulation of cAMP production (48, 49) in A_2AAR-expressing HEK293 cells. [³H]R-N⁶-(2-phenylisopropyl)adenosine ([³H]R-PIA, 42.6 Ci/mmol) was obtained from Moravek Biochemicals (Brea, CA). [³H](2-[p-(2-Carboxyethyl)phenylethylamino]-5′-N-ethylcarboxamidoadenosine) ([³H]CGS21680, 40.5 Ci/mmol) and [¹²⁵I]N⁶-(4-amino-3-iodobenzyl)adenosine-5′-N-methyluronamide ([¹²⁵I]I-AB-MECA, 2200 Ci/mmol) were purchased from Perkin-Elmer Life and Analytical Science (Boston, MA). Test compounds were prepared as 5 mM stock solutions in DMSO and stored frozen at −20 °C.

Cell Culture and Membrane Preparation

CHO cells stably expressing the recombinant hA₁ and hA₃Rs, and HEK-293 cells stably expressing the hA_2AAR were cultured in Dulbecco’s modified Eagle medium (DMEM) and F12 (1:1) supplemented with 10% fetal bovine serum, 100 units/mL penicillin, 100 μg/mL streptomycin, and 2 μmol/mL glutamine. In addition, 800 μg/mL Geneticin was added to the A_2A media, while 500 μg/mL hygromycin was added to the A₁ and A₃ media. After being harvested, cells were homogenized and suspended in PBS. Cells were then centrifuged at 240g for 5 min, and the pellet was resuspended in 50 mM Tris-HCl buffer (pH 7.5) containing 10 mM MgCl₂. The suspension was homogenized and was then ultracentrifuged at 14330g for 30 min at 4 °C. The resultant pellets were resuspended in Tris buffer and incubated with adenosine deaminase (3 units/mL) for 30 min at 37 °C. The suspension was homogenized with an electric homogenizer for 10 s, pipetted into 1 mL vials, and then stored at −80 °C until the binding experiments were conducted. The protein concentration was measured using the BCA protein assay kit from Thermo Scientific Pierce Protein Research Products (Rockford, IL). (50)

Binding Assays

The tested compounds were purchased from six different vendors (Enamine, ChemDiv, ChemBridge, Vitas-M, Pharmeks, and Asinex). The vendors had verified that each compound had ≥95% purity by liquid chromatography−mass spectrometry (LC−MS) or nuclear magnetic resonance (NMR) experiments. Into each tube in the binding assay was added 50 μL of increasing concentrations of the test ligand in Tris-HCl buffer (50 mM, pH 7.5) containing 10 mM MgCl₂, 50 μL of the appropriate agonist radioligand, and finally 100 μL of membrane suspension. For the A₁AR (22 μg of protein/tube) the radioligand used was [³H]R-PIA (final concentration of 3.5 nM). For the A_2AAR (20 μg/tube) the radioligand used was [³H]CGS21680 (10 nM). For the A₃AR (21 μg/tube) the radioligand used was [¹²⁵I]I-AB-MECA (0.34 nM). Nonspecific binding was determined using a final concentration of 10 μM unlabeled 5′-N-ethylcarboxamidoadenosine (NECA, 2) diluted with the buffer. The mixtures were incubated at 25 °C for 60 min in a shaking water bath. Binding reactions were terminated by filtration through Brandel GF/B filters under a reduced pressure using a M-24 cell harvester (Brandel, Gaithersburg, MD). Filters were washed three times with 3 mL of 50 mM ice-cold Tris-HCl buffer (pH 7.5). Filters for A₁ and A_2AAR binding were placed in scintillation vials containing 5 mL of Hydrofluor scintillation buffer and counted using a Perkin Elmer liquid scintillation analyzer (Tri-Carb 2810TR). Filters for A₃AR binding were counted using a Packard Cobra II γ-counter. The K_i values were determined using GraphPad Prism for all assays.

Cyclic AMP Accumulation Assay

Intracellular cyclic AMP (cAMP) levels were measured with a competitive protein binding method. (48, 49) CHO293 cells that expressed the recombinant human A_2AAR were harvested by trypsinization. After centrifugation and resuspension in medium, cells were planted in 24-well plates in 1.0 mL of medium. After 24 h, the medium was removed and cells were washed three times with 1 mL of DMEM containing 50 mM HEPES, pH 7.4. Cells were then treated with the test compound in the presence of rolipram (10 μM) and adenosine deaminase (3 units/mL), and incubation was continued for an additional 1 h. The reaction was terminated by removing the supernatant, and cells were lysed upon the addition of 200 μL of 0.1 M ice-cold HCl. The cell lysate was resuspended and stored at −20 °C. For determination of cyclic AMP production, protein kinase A (PKA) was incubated with [³H]cyclic AMP (2 nM) in K₂HPO₄/EDTA buffer (K₂HPO₄, 150 mM; EDTA, 10 mM), 20 μL of the cell lysate, and 30 μL of 0.1 M HCl or 50 μL of cyclic AMP solution (0−16 pmol/200 μL for standard curve). Bound radioactivity was separated by rapid filtration through Whatman GF/C filters and washed once with cold buffer. Bound radioactivity was measured by liquid scintillation spectrometry.

Counterscreen for Colloidal Inhibition

To control for artifactual inhibition by colloidal aggregation, we looked for particle formation by Dynamic Light Scattering (DLS) and by inhibition of two counterscreen enzymes, cruzain and AmpC β-lactamase. Concentrated DMSO stocks of compounds were diluted with filtered 50 mM KPi, pH 7.0. Measurements were made using a DynaPro MS/X (Wyatt Technology) with a 55 mW laser at 826.6 nm. The laser power was 100%, and the detector angle was 90°. Cruzain assays were performed in 100 mM sodium acetate, pH 5.5, containing 5 mM DTT with and without 0.1% Triton X-100. Compounds were incubated with 0.8 nM cruzain for 5 min, and reactions were initiated by adding the fluorogenic substrate Z-Phe-Arg-aminomethylcoumarin (Z-FR-AMC). The final reaction volume was 200 μL with cruzain at 0.4 nM and ZF-R-AMC at 2.5 μM. Final DMSO concentrations were 0.5%. To measure enzyme inhibition, the increase in fluorescence (excitation wavelength of 355 nm, emission wavelength of 460 nm) was recorded for 5 min in a microtiter plate spectrofluorimeter (Molecular Devices, FlexStation). Assays were performed in duplicate in 96-well plates, with controls measuring enzyme activity in the presence of DMSO. Activity was measured for seven different concentrations for each compound. Inhibition of AmpC β-lactamase was measured for the two best compounds identified here, compounds 9 and 11, to complement the cruzain assay results. Assays were performed in 50 mM potassium phosphate, pH 7.0. Compounds were incubated with 1 nM β-lactamase for 5 min, and reactions were initiated by adding the substrate CENTA to a final concentration 92 μM. The final reaction volume was 1 mL. To measure enzyme inhibition, the increase in absorbance at 405 nm was recorded for 5 min in a UV−vis spectrophotometer (Agilent). Assays were performed in duplicate in 1 mL cuvettes, with controls measuring enzyme activity in the presence of DMSO. Activity was measured at 10 μM, 0.1% DMSO.

Results and Discussion

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Molecular Docking Screen and Compound Selection

The program DOCK3.5.54 (16, 17) was used to screen 1.4 million commercially available “leadlike” molecules from the ZINC (33) database against the orthosteric site of the A_2A AR. On average, each molecule was sampled in 5000 orientations and, for each that fit, an average of 16 500 conformations; the receptor was held rigid. Each molecule was scored for electrostatic and van der Waals complementarity corrected for ligand desolvation. Molecules typically overlapped with the geometry of the crystallized antagonist, making a mixture of polar and hydrophobic interactions, packing deeply into the site (Figure 1). The 500 top-ranking molecules (Table S1, Supporting Information), 0.035% of the docking prioritized library, were analyzed visually for features that are not taken into account in the docking calculation. This is a standard procedure for all our docking screens in which each of the molecules is inspected for novelty, physical properties, and binding energy contributions that are not included in the docking scoring function. For example, compound 9 (Table 1) was chosen both because it complemented the site well and because there were several molecules with the same scaffold in the top 500 list of compounds (e.g., the molecules ranked 7, 31, 59, 104, 115, 135, 137, 172, 184, 199, and 278 in Table S1, Supporting Information). From this evaluation, 20 compounds representing diverse molecules (within the context of the top 500-ranking molecules) were prioritized for experimental testing.

Table 1. Ligand Structures and Experimental Data for the Seven Hits from the Docking Screen against the A₁, A_2A, and A₃ ARs

Rank in the docking screen.

Measured in three independent experiments.

The most similar compound annotated to ARs in WOMBAT (39) and ChEMBL. (40)

Tanimoto similarity coefficient to the closest annotated adenosine receptor ligand from ECFP4 fingerprints.

Radioligand Displacement Assays and Docking Hit Rate

The 20 compounds selected from the docking screen were tested for binding in a radioligand displacement assay. Seven of these molecules inhibited binding by ≥40% at 20 μM, corresponding to a “hit rate” of 35%. Subsequent dose−response curves were well-behaved, with K_i values varying from 200 nM to 8.8 μM (Table 1 and Figure 2). Four of the ligands, 9, 10, 11 and 13, were counterscreened for colloidal aggregation, a common mechanism of artifactual inhibition. (51) No colloidal particles were observed at 10 μM, by dynamic light scattering, for 9 and 13, nor did they inhibit cruzain at the same concentration. For compounds 10 and 11, particles were observed at 10 μM, but for 10 these appeared to be precipitant rather than colloids and this compound did not inhibit cruzain up to 10 μM. For compound 11 particles were observed at 10 μM, as was enzyme inhibition, but this inhibition was not reversible by detergent, inconsistent with colloidal aggregation. Furthermore, no inhibition of AmpC β-lactamase was observed up to 10 μM for 9 and 11. Taken together with the well-behaved dose−response curves (Figure 2), these results indicate that the molecules are well behaved, classical binding ligands.

Figure 2. Representative dose−response curves for displacement of binding of the radiolabeled A_2A AR agonist 3 by compounds 9, 10, and 11.

All seven docking hits are specific for the A_2A AR versus the related A₁ and A₃ subtypes (Table 1). Notably, our most potent ligand, compound 11, is also the most specific with over 50-fold higher affinity at the A_2A AR. We therefore investigated five of its analogues not picked in the first round of docking that also fit well into the site (compounds 14−18, Table 2). Four of the analogues were found to bind to the A_2A AR with submicromolar affinities, and these molecules also had an improved A_2A/A₁ subtype selectivity. From these results, the prospects of identifying specific high-affinity A_2A antagonists in this new class of compounds appear promising.

Table 2. Binding Affinities and Structures of Five Analogues to Compound 11 in Radioligand Binding Assays at A₁, A_2A, and A₃ ARs

Measured in three independent experiments.

To put the results from this docking screen in perspective, our laboratory considers a high-throughput docking screen to be successful if a hit rate of 5% with ligand affinities in the micromolar range can be achieved. For example, we tested 56 compounds from a docking screen against AmpC β-lactamase and found one compound with a K_i value better than 100 μM, corresponding to a hit rate of 2%; (29) this inhibitor had a K_i value of 26 μM (Table 3). In the case of the A_2A AR we observe 10-fold higher hit rate and the affinities of the hits are 10- to 100-fold better. Intriguingly, similar results were obtained in two docking screens against the other pharmaceutically relevant GPCR for which a crystallographic structure has been solved, the β₂ adrenergic receptor. (19, 20) Kolb et al. identified six previously unknown ligands of the β₂ adrenergic receptor, a 24% hit rate, with affinities as high as 9 nM. (19) It may be that GPCRs are particularly well-suited for structure-based docking screens, a point to which we will return.

Table 3. Target Library Bias and Docking Hit Rates

		representative DOCK screen
target	no. of ZINC molecules similar to known ligands^a	hit rate^b (%)	best potency^c (nM)
adenosine receptors	4240	35	200
adrenergic receptors	4146	24	9 (19)
adenylyl cyclases	565	4	50000 (55)
AmpC β-lactamase	545	2−5	26000 (29)

ZINC leadlike molecules with at least 10⁻¹⁰P values to annotated target ligands in WOMBAT using the similarity ensemble approach (SEA).

(Number of true ligands)/(number of predictions tested experimentally).

The affinity of the ligand with the best potency from the docking screen.

Predicted Binding Modes, Novelty, and Efficacy of the Discovered A_2A AR Ligands

All seven of the new ligands are predicted to interact with the key recognition residue Asn253 in transmembrane helix 6 and many also hydrogen-bond with the carboxylate of Glu169 in extracellular loop 2, both in the orthosteric site of the receptor (Figure 1). The importance of interactions with Asn253 was identified early in our docking screens. We found that increasing the dipole moment of the Asn253 side chain amide, a technique we employ frequently, substantially increased the enrichment of known A_2A AR ligands among a database of decoys in control calculations. Asn253 is conserved in all four AR receptor subtypes and has also been found to be a crucial interaction partner for both agonists and antagonists in mutagenesis studies. (52)

Whereas all the seven ligands are previously uncharacterized for the A_2A AR, some of them bear known chemotypes. To quantify their novelty, or lack of it, we calculated the similarity of each molecule to 7500 known AR ligands from the WOMBAT and ChEMBL databases using pairwise Tanimoto coefficients (T_c, ECFP4 fingerprints) (Table 1). Ligand 12 resembles members of the xanthine class of antagonists, while compound 7 resembles certain quinazoline (53) ligands. Conversely, whereas compounds 10, 11, and 13 do conserve several moieties with known ligands, they also differ substantially from them, with T_c values of 0.3 to the closest annotated ligand. Nevertheless, they complement the site well both sterically and electrostatically (Figure 1). The potency of these molecules suggests that they may merit further study as new lead families for antagonists of the A_2A AR.

To determine the efficacy of the compounds, their ability to inhibit intracellular cAMP production induced by agonist 3 was tested. No stimulation of cAMP production was detected for any of the molecules, while a clear displacement of agonist function was observed for the two most potent compounds, 9 and 11 (Figure 3). All seven of the new ligands are thus almost certainly A_2A antagonists, as is the cocrystallized ligand. Intriguingly, this efficacy bias was also observed in the docking screens against the β₂ adrenergic receptor, where only inverse agonists were found against the structure crystallized with the inverse agonist carazolol. In docking to rigid GPCR structures, the protein conformation may bias the screen toward molecules with the same efficacy as the cocrystallized ligand. This represents a challenge to our ability to exploit these structures for mechanisms of action, such as agonism, not represented in the experimental structure. To further investigate this, we determined the rank of two agonists, 1 and 2 (Chart 1), that were present in the set of commercially available molecules screened against the A_2A AR binding site. Whereas multiple known antagonists would have been ranked among the top 500 molecules in the docking screen, these two agonists were ranked 951 057 and 919 993, respectively.

Figure 3. Functional assay based on measuring the production of cAMP for 3 (control), a potent A_2A AR agonist, with or without 10 μM 9 or **11.** The dose−response curve is shifted for both compounds, as expected in the case of competitive antagonistic inhibition. The % activation refers to production of cAMP normalized to the effect of 3 at 100 μM.

Is There Library Bias toward GPCR Chemotypes in Chemical Libraries?

Returning to one of the questions that motivated this study, the structure-based screen against the A_2A AR returned a diverse set of ligands dissimilar to those previously characterized, as well as several similar to known ligands, and did so with a hit rate of 35%. Not only is this hit rate much higher than we have come to expect for enzyme targets screened with the same approach, but the new antagonists were also close to 100-fold more potent than we have come to expect for our docking “hits”. Furthermore, these results are strikingly similar to those observed in docking screens against the β₂ adrenergic GPCR. (19, 20) To what may these unusually high hit rates and affinities be attributed?

Family A GPCRs like the A_2A AR are the targets for a substantial fraction of marketed drugs, and this partly reflects the quality of their sites for specific recognition of small molecules. Largely buried from bulk solvent, these sites can almost completely enclose a “druglike” molecule and can do so with a mixture of nonpolar and polar interactions. Consequently, a large and sustained medicinal chemistry effort has focused on these targets, and by now even putatively unbiased libraries, like ZINC, have become populated with molecules bearing “GPCR-like” chemotypes. This also reflects a bias toward naturally occurring molecules in our screening libraries. (54) Indeed, Kolb et al. estimated that there were 3−12 times as many small molecules that were similar to GPCR ligands in the ZINC leadlike set compared to other common drug targets such as kinases, proteases, and ligand-gated ion channels. (19) To make this comparison more specific and relevant to the adenosine receptor versus other docking targets that we ourselves have worked, we investigated the library bias in ZINC for the adrenergic and adenosine receptors together with two other targets for which we have observed much lower hit rates and affinities (19, 29, 55) (Table 3). The number of molecules in the ZINC leadlike set that are similar to the ligands of these targets was estimated using SEA, (54) insisting on a P value of 10⁻¹⁰ or better; acceptable molecules had also to resemble the annotated ligands in their physical properties (see Methods). Over 4000 small molecules resemble ligands annotated to the ARs and adrenergic receptors in the WOMBAT (39) database, almost 10-fold more than found for the enzymes adenylyl cyclase and AmpC β-lactamase, against which, correspondingly, our docking hit rates and affinities have been 10- to 100-fold lower. Thus, it is the convolution of the high “ligand-ability” of the orthosteric sites and the many GPCR-like chemotypes in our libraries that makes the adrenergic and adenosine receptors so fruitful for structure-based techniques.

Note Added after Initial Review of This Paper

After this paper was submitted for review, a paper by Abagyan, Stevens, and colleagues appeared that also targeted the A_2A AR for novel inhibitor discovery, also using a molecular docking screen. (56) As here, Abagyan et al. also observed a very substantial hit rate with high affinities (indeed, both the affinities and hit rates were slightly better than those we observe). Whereas the compounds discovered in the two screens were substantially different, the observation of the high hit rates and, by screening standards, high affinity “hits” is consistent with the high “ligand-ability” of the class A GPCRs and the fortuitous library bias toward them, and this is among the important conclusions of this study.

Supporting Information

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Table S1 of structures of the 500 top-ranking molecules from the docking screen. This material is available free of charge via the Internet at http://pubs.acs.org.

jm100240h_si_001.pdf (2.22 MB)

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Author Information

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Corresponding Authors
- Brian K. Shoichet - Department of Pharmaceutical Chemistry, University of California, 1700 4th Street, Box 2550, San Francisco, California 94158; Email: [email protected] [email protected]
- Kenneth A. Jacobson - Molecular Recognition Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland 20892; Email: [email protected] [email protected]
Authors
- Jens Carlsson - Department of Pharmaceutical Chemistry, University of California, 1700 4th Street, Box 2550, San Francisco, California 94158
- Lena Yoo - Molecular Recognition Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland 20892
- Zhan-Guo Gao - Molecular Recognition Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland 20892
- John J. Irwin - Department of Pharmaceutical Chemistry, University of California, 1700 4th Street, Box 2550, San Francisco, California 94158

Acknowledgment

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This work is supported by NIH Grant GM59957 (to B.K.S.), NIDDK Intramural Research Program (to K.A.J.), and a fellowship from the Knut and Alice Wallenberg Foundation (to J.C.). We thank A. Doak for aggregation assays and members of the Shoichet lab for docking “hit-list” evaluation. We thank Tudor Oprea for access to the WOMBAT database and John Overington for a prerelease version of the ChEMBL database.

References

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Overington, J. P.; Al-Lazikani, B.; Hopkins, A. L. How many drug targets are there? Nat. Rev. Drug Discovery 2006, 5, 993– 996
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How many drug targets are there?
Overington, John P.; Al-Lazikani, Bissan; Hopkins, Andrew L.
Nature Reviews Drug Discovery (2006), 5 (12), 993-996CODEN: NRDDAG; ISSN:1474-1776. (Nature Publishing Group)
A review. For the past decade, the no. of mol. targets for approved drugs has been debated. Here, we reconcile apparently contradictory previous reports into a comprehensive survey, and propose a consensus no. of current drug targets for all classes of approved therapeutic drugs. One striking feature is the relatively const. historical rate of target innovation (the rate at which drugs against new targets are launched); however, the rate of developing drugs against new families is significantly lower. The recent approval of drugs that target protein kinases highlights two addnl. trends: an emerging realization of the importance of polypharmacol., and also the power of a gene-family-led approach in generating novel and important therapies.
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Cherezov, V.; Rosenbaum, D. M.; Hanson, M. A.; Rasmussen, S. G. F.; Thian, F. S.; Kobilka, T. S.; Choi, H. J.; Kuhn, P.; Weis, W. I.; Kobilka, B. K.; Stevens, R. C. High-resolution crystal structure of an engineered human beta(2)-adrenergic G protein-coupled receptor Science 2007, 318, 1258– 1265
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High-Resolution Crystal Structure of an Engineered Human β2-Adrenergic G Protein-Coupled Receptor
Cherezov, Vadim; Rosenbaum, Daniel M.; Hanson, Michael A.; Rasmussen, Soren G. F.; Thian, Foon Sun; Kobilka, Tong Sun; Choi, Hee-Jung; Kuhn, Peter; Weis, William I.; Kobilka, Brian K.; Stevens, Raymond C.; Takeda, S.; Kadowaki, S.; Haga, T.; Takaesu, H.; Mitaku, S.; Fredriksson, R.; Lagerstrom, M. C.; Lundin, L. G.; Schioth, H. B.; Pierce, K. L.; Premont, R. T.; Lefkowitz, R. J.; Lefkowitz, R. J.; Shenoy, S. K.; Rosenbaum, D. M.
Science (Washington, DC, United States) (2007), 318 (5854), 1258-1265CODEN: SCIEAS; ISSN:0036-8075. (American Association for the Advancement of Science)
Second extracellular loop, which in the β2-adrenergic receptor contains an unusual pair of disulfide bonds and an extra helix. This loop and the absence Heterotrimeric guanine nucleotide-binding protein (G protein)-coupled receptors constitute the largest family of eukaryotic signal transduction proteins that communicate across the membrane. We report the crystal structure of a human β2-adrenergic receptor-T4 lysozyme fusion protein bound to the partial inverse agonist carazolol at 2.4 angstrom resoln. The structure provides a high-resoln. view of a human G protein-coupled receptor bound to a diffusible ligand. Ligand-binding site accessibility is enabled by the second extracellular loop, which is held out of the binding cavity by a pair of closely spaced disulfide bridges and a short helical segment within the loop. Cholesterol, a necessary component for crystn., mediates an intriguing parallel assocn. of receptor mols. in the crystal lattice. Although the location of carazolol in the β2-adrenergic receptor is very similar to that of retinal in rhodopsin, structural differences in the ligand-binding site and other regions highlight the challenges in using rhodopsin as a template model for this large receptor family.
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Rosenbaum, D. M.; Cherezov, V.; Hanson, M. A.; Rasmussen, S. G. F.; Thian, F. S.; Kobilka, T. S.; Choi, H. J.; Yao, X. J.; Weis, W. I.; Stevens, R. C.; Kobilka, B. K. GPCR engineering yields high-resolution structural insights into beta(2)-adrenergic receptor function Science 2007, 318, 1266– 1273
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Warne, T.; Serrano-Vega, M. J.; Baker, J. G.; Moukhametzianov, R.; Edwards, P. C.; Henderson, R.; Leslie, A. G. W.; Tate, C. G.; Schertler, G. F. X. Structure of a beta(1)-adrenergic G-protein-coupled receptor Nature 2008, 454, 486– 491
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Jaakola, V. P.; Griffith, M. T.; Hanson, M. A.; Cherezov, V.; Chien, E. Y. T.; Lane, J. R.; IJzerman, A. P.; Stevens, R. C. The 2.6 angstrom crystal structure of a human A(2A) adenosine receptor bound to an antagonist Science 2008, 322, 1211– 1217
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The 2.6 Angstrom Crystal Structure of a Human A2A Adenosine Receptor Bound to an Antagonist
Jaakola, Veli-Pekka; Griffith, Mark T.; Hanson, Michael A.; Cherezov, Vadim; Chien, Ellen Y. T.; Lane, J. Robert; IJzerman, Adriaan P.; Stevens, Raymond C.
Science (Washington, DC, United States) (2008), 322 (5905), 1211-1217CODEN: SCIEAS; ISSN:0036-8075. (American Association for the Advancement of Science)
The adenosine class of heterotrimeric guanine nucleotide-binding protein (G protein)-coupled receptors (GPCRs) mediates the important role of extracellular adenosine in many physiol. processes and is antagonized by caffeine. The authors have detd. the crystal structure of the human A2A adenosine receptor, in complex with a high-affinity subtype-selective antagonist, ZM241385, to 2.6 angstrom resoln. Four disulfide bridges in the extracellular domain, combined with a subtle repacking of the transmembrane helixes relative to the adrenergic and rhodopsin receptor structures, define a pocket distinct from that of other structurally detd. GPCRs. The arrangement allows for the binding of the antagonist in an extended conformation, perpendicular to the membrane plane. The binding site highlights an integral role for the extracellular loops, together with the helical core, in ligand recognition by this class of GPCRs and suggests a role for ZM241385 in restricting the movement of a tryptophan residue important in the activation mechanism of the class A receptors.
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Congreve, M.; Marshall, F. The impact of GPCR structures on pharmacology and structure-based drug design Br. J. Pharmacol. 2010, 159, 986– 996
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The impact of GPCR structures on pharmacology and structure-based drug design
Congreve, Miles; Marshall, Fiona
British Journal of Pharmacology (2010), 159 (5), 986-996CODEN: BJPCBM; ISSN:1476-5381. (Wiley-Blackwell)
A review. After many years of effort, recent tech. breakthroughs have enabled the X-ray crystal structures of three G-protein-coupled receptors (GPCRs) (β1 and β2 adrenergic and adenosine A2a) to be solved in addn. to rhodopsin. GPCRs, like other membrane proteins, have lagged behind sol. drug targets such as kinases and proteases in the no. of structures available and the level of understanding of these targets and their interaction with drugs. The availability of increasing nos. of structures of GPCRs is set to greatly increase our understanding of some of the key issues in GPCR biol. In particular, what constitutes the different receptor conformations that are involved in signaling and the mol. changes which occur upon receptor activation. How future GPCR structures might alter our views on areas such as agonist-directed signaling and allosteric regulation as well as dimerization is discussed. Knowledge of crystal structures in complex with small mols. will enable techniques in drug discovery and design, which have previously only been applied to sol. targets, to now be used for GPCR targets. These methods include structure-based drug design, virtual screening and fragment screening. This review considers how these methods have been used to address problems in drug discovery for kinase and protease targets and therefore how such methods are likely to impact GPCR drug discovery in the future.
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Moro, S.; Gao, Z. G.; Jacobson, K. A.; Spalluto, G. Progress in the pursuit of therapeutic adenosine receptor antagonists Med. Res. Rev. 2006, 26, 131– 159
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Progress in the pursuit of therapeutic Adenosine receptor antagonists
Moro, Stefano; Gao, Zhan-Guo; Jacobson, Kenneth A.; Spalluto, Giampiero
Medicinal Research Reviews (2006), 26 (2), 131-159CODEN: MRREDD; ISSN:0198-6325. (John Wiley & Sons, Inc.)
A review. Ever since the discovery of the hypotensive and bradycardiac effects of adenosine, adenosine receptors continue to represent promising drug targets. First, this is due to the fact that the receptors are expressed in a large variety of tissues. In particular, the actions of adenosine (or methylxanthine antagonists) in the central nervous system, in the circulation, on immune cells, and on other tissues can be beneficial in certain disorders. Second, there exists a large no. of ligands, which have been generated by introducing several modifications in the structure of the lead compds. (adenosine and methylxanthine), some of them highly specific. Four adenosine receptor subtypes (A1, A2A, A2B, and A3) have been cloned and pharmacol. characterized, all of which are G protein-coupled receptors. Adenosine receptors can be distinguished according to their preferred mechanism of signal transduction: A1 and A3 receptors interact with pertussis toxin-sensitive G proteins of the Gi and Go family; the canonical signaling mechanism of the A2A and of the A2B receptors is stimulation of adenylyl cyclase via Gs proteins. In addn. to the coupling to adenylyl cyclase, all four subtypes may pos. couple to phospholipase C via different G protein subunits. The development of new ligands, in particular, potent and selective antagonists, for all subtypes of adenosine receptors has so far been directed by traditional medicinal chem. The availability of genetic information promises to facilitate understanding of the drug-receptor interaction leading to the rational design of a potentially therapeutically important class of drugs. Moreover, mol. modeling may further rationalize obsd. interactions between the receptors and their ligands. In this review, we will summarize the most relevant progress in developing new therapeutic adenosine receptor antagonists.
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Jacobson, K. A.; Gao, Z. G. Adenosine receptors as therapeutic targets Nat. Rev. Drug Discovery 2006, 5, 247– 264
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Adenosine receptors as therapeutic targets
Jacobson, Kenneth A.; Gao, Zhan-Guo
Nature Reviews Drug Discovery (2006), 5 (3), 247-264CODEN: NRDDAG; ISSN:1474-1776. (Nature Publishing Group)
A review. Adenosine receptors are major targets of caffeine, the most commonly consumed drug in the world. There is growing evidence that they could also be promising therapeutic targets in a wide range of conditions, including cerebral and cardiac ischemic diseases, sleep disorders, immune and inflammatory disorders and cancer. After more than three decades of medicinal chem. research, a considerable no. of selective agonists and antagonists of adenosine receptors have been discovered, and some have been clin. evaluated, although none has yet received regulatory approval. However, recent advances in the understanding of the roles of the various adenosine receptor subtypes, and in the development of selective and potent ligands, as discussed in this review, have brought the goal of therapeutic application of adenosine receptor modulators considerably closer.
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Sebastiao, A. M.; Ribeiro, J. A. Adenosine receptors and the central nervous system Handb. Exp. Pharmacol. 2009, 471– 534
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Adenosine receptors and the central nervous system
Sebastiao, Ana M.; Ribeiro, Joaquim A.
Handbook of Experimental Pharmacology (2009), 193 (Adenosine Receptors in Health and Disease), 471-534CODEN: HEPHD2; ISSN:0171-2004. (Springer GmbH)
A review. The adenosine receptors (ARs) in the nervous system act as a kind of "go-between" to regulate the release of neurotransmitters (this includes all known neurotransmitters) and the action of neuromodulators (e.g., neuropeptides, neurotrophic factors). Receptor-receptor interactions and AR-transporter interplay occur as part of the adenosine's attempt to control synaptic transmission. A2AARs are more abundant in the striatum and A1ARs in the hippocampus, but both receptors interfere with the efficiency and plasticity-regulated synaptic transmission in most brain areas. The omnipresence of adenosine and A2A and A1 ARs in all nervous system cells (neurons and glia), together with the intensive release of adenosine following insults, makes adenosine a kind of "maestro" of the tripartite synapse in the homeostatic coordination of the brain function. Under physiol. conditions, both A2A and A1 ARs play an important role in sleep and arousal, cognition, memory and learning, whereas under pathol. conditions (e.g., Parkinson's disease, Alzheimer's disease, amyotrophic lateral sclerosis, stroke, epilepsy, drug addiction, pain, schizophrenia, depression), ARs operate a time/circumstance window where in some circumstances A1AR agonists may predominate as early neuroprotectors, and in other circumstances A2AAR antagonists may alter the outcomes of some of the pathol. deficiencies. In some circumstances, and depending on the therapeutic window, the use of A2AAR agonists may be initially beneficial; however, at later time points, the use of A2AAR antagonists proved beneficial in several pathologies. Since selective ligands for A1 and A2A ARs are now entering clin. trials, the time has come to det. the role of these receptors in neurol. and psychiatric diseases and identify therapies that will alter the outcomes of these diseases, therefore providing a hopeful future for the patients who suffer from these diseases.
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Blackburn, M. R.; Vance, C. O.; Morschl, E.; Wilson, C. N. Adenosine receptors and inflammation Handb. Exp. Pharmacol. 2009, 215– 269
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Adenosine receptors and inflammation
Blackburn, Michael R.; Vance, Constance O.; Morschl, Eva; Wilson, Constance N.
Handbook of Experimental Pharmacology (2009), 193 (Adenosine Receptors in Health and Disease), 215-269CODEN: HEPHD2; ISSN:0171-2004. (Springer GmbH)
A review. Extracellular adenosine is produced in a coordinated manner from cells following cellular challenge or tissue injury. Once produced, it serves as an autocrine- and paracrine-signaling mol. through its interactions with seven-membrane-spanning G-protein-coupled adenosine receptors. These signaling pathways have widespread physiol. and pathophysiol. functions. Immune cells express adenosine receptors and respond to adenosine or adenosine agonists in diverse manners. Extensive in vitro and in vivo studies have identified potent anti-inflammatory functions for all of the adenosine receptors on many different inflammatory cells and in various inflammatory disease processes. In addn., specific proinflammatory functions have also been ascribed to adenosine receptor activation. The potent effects of adenosine signaling on the regulation of inflammation suggest that targeting specific adenosine receptor activation or inactivation using selective agonists and antagonists could have important therapeutic implications in numerous diseases. This review is designed to summarize the current status of adenosine receptor signaling in various inflammatory cells and in models of inflammation, with an emphasis on the advancement of adenosine-based therapeutics to treat inflammatory disorders.
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Cristalli, G.; Muller, C. E.; Volpini, R. Recent developments in adenosine A2A receptor ligands Handb. Exp. Pharmacol. 2009, 59– 98
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Recent developments in adenosine A2A receptor ligands
Cristalli, Gloria; Muller, Christa E.; Volpini, Rosaria
Handbook of Experimental Pharmacology (2009), 193 (Adenosine Receptors in Health and Disease), 59-98CODEN: HEPHD2; ISSN:0171-2004. (Springer GmbH)
A review. The development of potent and selective agonists and antagonists of adenosine receptors (ARs) has been a target of medicinal chem. research for several decades, and recently the US Food and Drug Administration has approved Lexiscan, an adenosine deriv. substituted at the 2 position, for use as a pharmacol. stress agent in radionuclide myocardial perfusion imaging. Currently, some other adenosine A2A receptor (A2AAR) agonists and antagonists are undergoing preclin. testing and clin. trials. While agonists are potent antiinflammatory agents also showing hypotensive effects, antagonists are being developed for the treatment of Parkinson's disease. However, since there are still major problems in this field, including side effects, low brain penetration (for the targeting of CNS diseases), short half-life, or lack of in vivo effects, the design and development of new AR ligands is a hot research topic. This review presents an update on the medicinal chem. of A2AAR agonists and antagonists, and stresses the strong need for more selective ligands at the human A2AAR subtype, in particular in the case of agonists.
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Poucher, S. M.; Keddie, J. R.; Singh, P.; Stoggall, S. M.; Caulkett, P. W. R.; Jones, G.; Collis, M. G. The in-vitro pharmacology of Zm-241385, a potent, nonxanthine, a(2a) selective adenosine receptor antagonist Br. J. Pharmacol. 1995, 115, 1096– 1102
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The in vitro pharmacology of ZM 241385, a potent, non-xanthine, A2a selective adenosine receptor antagonist
Poucher, S. M.; Keddie, J. R.; Singh, P.; Stoggall, S. M.; Caulkett, P. W. R.; Jones, G.; Collis, M. G.
British Journal of Pharmacology (1995), 115 (6), 1096-102CODEN: BJPCBM; ISSN:0007-1188. (Macmillan Scientific & Medical Division)
This paper describes the in vitro pharmacol. of ZM 241385 (4-(2-[7-amino-2-(2-furyl) [1,2,4]-triazolo[2,3-a][1,3,5]triazin-5-ylamino]ethyl)phenol), a novel non-xanthine adenosine receptor antagonist with selectivity for the A2 receptor subtype. ZM 241385 had high affinity for A2a receptors. In rat pheochromocytoma cell membranes, ZM 241385 displaced binding of tritiated 5'-N-ethylcarboxamidoadenosine (NECA) with a pIC50 of 9.52, (95% confidence limits, c.l., 9.02-10.02). In guinea-pig isolated Langendorff hearts, ZM 241385 antagonized vasodilation of the coronary bed produced by 2-chloroadenosine (2-CADO) and 2-[p-(2-carboxyethyl) phenylamino]-5'-N-ethylcarboxamidoadenosine (CGS21680) with pA2 values of 8.57 (c.l., 8.45-8.68) and 9.02 (c.l., 8.79-9.24) resp. ZM 241385 had low potency at A2b receptors and antagonized the relaxant effects of adenosine in the guinea-pig aorta with a pA2 of 7.06 (c.l., 6.92-7.19). ZM 241385 had a low affinity at A1 receptors. In rat cerebral cortex membranes it displayed tritiated R-phenylisopropyladenosine (R-PIA) with a pIC50 of 5.69 (c.l., 5.57-5.81). ZM 241385 antagonized the bradycardic action of 2-CADO in guinea-pig atria with a pA2 of 5.95 (c.l., 5.72-6.18). ZM 241385 had low affinity for A3 receptors. At cloned rat A3 receptors expressed in chinese hamster ovary cells, it displayed iodinated aminobenzyl-5'-N-methylcarboxamido adenosine (AB-MECA) with a pIC50 of 3.82 (c.l., 3.67-4.06). ZM 241385 had no significant addnl. pharmacol. effects on the isolated tissues used in these studies at concns. three orders of magnitude greater than those which block A2a receptors. At 10 μM it displayed only minor inhibition of the bradycardic effects in guinea-pig atria to some concns. of carbachol. At 10 μM, ZM 241385 had a small inhibitory effect on relaxant effects of isoprenaline in guinea-pig aorta but no effect on sodium nitrite-induced relaxation. ZM 241385 (100 μM) was without effect on phenylephrine-induced tone in guinea-pig aorta. ZM 241385 (10 μM) had no inhibitory effect on rat hepatocyte phosphodiesterase types I, II, III and IV but caused a small inhibition of the calcium calmodulin-activated type I enzyme. ZM 241385 is the most selective adenosine A2a receptor antagonist yet described and is therefore a useful tool for characterization of responses mediated by A2 adenosine receptors.
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Degen, J.; Rarey, M. FlexNovo: structure-based searching in large fragment spaces ChemMedChem 2006, 1, 854– 868
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Jones, G.; Willett, P.; Glen, R. C.; Leach, A. R.; Taylor, R. Development and validation of a genetic algorithm for flexible docking J. Mol. Biol. 1997, 267, 727– 748
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Development and validation of a genetic algorithm for flexible docking
Jones, Gareth; Willett, Peter; Glen, Robert C.; Leach, Andrew R.; Taylor, Robin
Journal of Molecular Biology (1997), 267 (3), 727-748CODEN: JMOBAK; ISSN:0022-2836. (Academic)
Prediction of small mol. binding modes to macromols. of known three-dimensional structure is a problem of paramount importance in rational drug design (the "docking" problem). We report the development and validation of the program GOLD (Genetic Optimization for Ligand Docking). GOLD is an automated ligand docking program that uses a genetic algorithm to explore the full range of ligand conformational flexibility with partial flexibility of the protein and satisfies the fundamental requirement that the ligand must displace loosely bound water on binding. Numerous enhancements and modifications have been applied to the original technique resulting in a substantial increase in the reliability and the applicability of the algorithm. The advanced algorithm has been tested on a dataset of 100 complexes extd. from the Brookhaven Protein Data Bank. When used to dock the ligand back into the binding site, GOLD achieved a 71% success rate in identifying the exptl. binding mode.
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Kairys, V.; Fernandes, M. X.; Gilson, M. K. Screening drug-like compounds by docking to homology models: a systematic study J. Chem. Inf. Model. 2006, 46, 365– 379
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Screening Drug-Like Compounds by Docking to Homology Models: A Systematic Study
Kairys, Visvaldas; Fernandes, Miguel X.; Gilson, Michael K.
Journal of Chemical Information and Modeling (2006), 46 (1), 365-379CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
In the absence of an exptl. solved structure, a homol. model of a protein target can be used instead for virtual screening of drug candidates by docking and scoring. This approach poses a no. of questions regarding the choice of the template to use in constructing the model, the accuracy of the screening results, and the importance of allowing for protein flexibility. The present study addresses such questions with compd. screening calcns. for multiple homol. models of five drug targets. A central result is that docking to homol. models frequently yields enrichments of known ligands as good as that obtained by docking to a crystal structure of the actual target protein. Interestingly, however, std. measures of the similarity of the template used to build the homol. model to the targeted protein show little correlation with the effectiveness of the screening calcns., and docking to the template itself often is as successful as docking to the corresponding homol. model. Treating key side chains as mobile produces a modest improvement in the results. The reasons for these sometimes unexpected results, and their implications for future methodol. development, are discussed.
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Lorber, D. M.; Shoichet, B. K. Flexible ligand docking using conformational ensembles Protein Sci. 1998, 7, 938– 950
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Flexible ligand docking using conformational ensembles
Lorber, David M.; Shoichet, Brian K.
Protein Science (1998), 7 (4), 938-950CODEN: PRCIEI; ISSN:0961-8368. (Cambridge University Press)
Mol. docking algorithms suggest possible structures for mol. complexes. They are used to model biol. function and to discover potential ligands. A present challenge for docking algorithms is the treatment of mol. flexibility. Here, the rigid body program, DOCK, is modified to allow it to rapidly fit multiple conformations of ligands. Conformations of a given mol. are pre-calcd. in the same frame of ref., so that each conformer shares a common rigid fragment with all other conformations. The ligand conformers are then docked together, as an ensemble, into a receptor binding site. This takes advantage of the redundancy present in differing conformers of the same mol. The algorithm was tested using three org. ligand protein systems and two protein-protein systems. Both the bound and unbound conformations of the receptors were used. The ligand ensemble method found conformations that resembled those detd. in X-ray crystal structures (RMS values typically less than 1.5 Å). To test the method's usefulness for inhibitor discovery, multi-compd. and multi-conformer databases were screened for compds. known to bind to dihydrofolate reductase and compds. known to bind to thymidylate synthase. In both cases, known inhibitors and substrates were identified in conformations resembling those obsd. exptl. The ligand ensemble method was 100-fold faster than docking a single conformation at a time and was able to screen a database of over 34 million conformations from 117,000 mols. in one to four CPU days on a workstation.
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Lorber, D. M.; Shoichet, B. K. Hierarchical docking of databases of multiple ligand conformations Curr. Top. Med. Chem. 2005, 5, 739– 749
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Hierarchical docking of databases of multiple ligand conformations
Lorber, David M.; Shoichet, Brian K.
Current Topics in Medicinal Chemistry (Sharjah, United Arab Emirates) (2005), 5 (8), 739-749CODEN: CTMCCL; ISSN:1568-0266. (Bentham Science Publishers Ltd.)
Ligand flexibility is an important problem in mol. docking and virtual screening. To address this challenge, we investigate a hierarchical pre-organization of multiple conformations of small mols. Such organization of pre-calcd. conformations removes the exploration of ligand conformational space from the docking calcn. and allows for concise representation of what can be thousands of conformations. The hierarchy also recognizes and prunes incompatible conformations early in the calcn., eliminating redundant calcns. of fit. We investigate the method by docking the MDL Drug Data Report (MDDR), an annotated database of 100,000 mols., into apo and holo forms of 7 unrelated targets. This annotated database allows us to track the ranking of tens to hundreds of annotated ligands in each of the docking systems. The binding sites and database are prepd. in an automated fashion in an attempt to remove some human bias from the calcns. Many thousands of explicit and implicit ligand conformations may be docked in calcns. not much longer than required for single conformer docking. As long as internal energies are not considered, recombination with the hierarchy is additive as the no. of degrees of freedom is increased. Mols. with even millions of conformations can be docked in a few minutes on a single desktop computer.
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Zavodszky, M. I.; Kuhn, L. A. Side-chain flexibility in protein−ligand binding: the minimal rotation hypothesis Protein Sci. 2005, 14, 1104– 1114
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Side-chain flexibility in protein-ligand binding: The minimal rotation hypothesis
Zavodszky, Maria I.; Kuhn, Leslie A.
Protein Science (2005), 14 (4), 1104-1114CODEN: PRCIEI; ISSN:0961-8368. (Cold Spring Harbor Laboratory Press)
The goal of this work is to learn from nature about the magnitudes of side-chain motions that occur when proteins bind small org. mols. and model these motions to improve the prediction of protein-ligand complexes. Following anal. of protein side-chain motions upon ligand binding in 63 complexes, we tested the ability of the docking tool SLIDE to model these motions without being restricted to rotameric transitions or deciding which side chains should be considered as flexible. The model tested is that side-chain conformational changes involving more atoms or larger rotations are likely to be more costly and less prevalent than small motions due to energy barriers between rotamers and the potential of large motions to cause new steric clashes. Accordingly, SLIDE adjusts the protein and ligand side groups as little as necessary to achieve steric complementarity. We tested the hypothesis that small motions are sufficient to achieve good dockings using 63 ligands and the apo structures of 20 different proteins and compared SLIDE side-chain rotations to those exptl. obsd. None of these proteins undergoes major main-chain conformational change upon ligand binding, ensuring that side-chain flexibility modeling is not required to compensate for main-chain motions. Although more frugal in the no. of side-chain rotations performed, this model substantially mimics the exptl. obsd. motions. Most side chains do not shift to a new rotamer, and small motions are both necessary and sufficient to predict the correct binding orientation and most protein-ligand interactions for the 20 proteins analyzed.
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Kolb, P.; Rosenbaum, D. M.; Irwin, J. J.; Fung, J. J.; Kobilka, B. K.; Shoichet, B. K. Structure-based discovery of beta(2)-adrenergic receptor ligands Proc. Natl. Acad. Sci. U.S.A. 2009, 106, 6843– 6848
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Structure-based discovery of β2-adrenergic receptor ligands
Kolb, Peter; Rosenbaum, Daniel M.; Irwin, John J.; Fung, Juan Jose; Kobilka, Brian K.; Shoichet, Brian K.
Proceedings of the National Academy of Sciences of the United States of America (2009), 106 (16), 6843-6848CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)
Aminergic G protein-coupled receptors (GPCRs) have been a major focus of pharmaceutical research for many years. Due partly to the lack of reliable receptor structures, drug discovery efforts have been largely ligand-based. The recently detd. X-ray structure of the β2-adrenergic receptor offers an opportunity to investigate the advantages and limitations inherent in a structure-based approach to ligand discovery against this and related GPCR targets. Approx. 1 million com. available, "lead-like" mols. were docked against the β2-adrenergic receptor structure. On testing of 25 high-ranking mols., 6 were active with binding affinities <4 μM, with the best mol. binding with a Ki of 9 nM (95% confidence interval 7-10 nM). Five of these mols. were inverse agonists. The high hit rate, the high affinity of the most potent mol., the discovery of unprecedented chemotypes among the new inhibitors, and the apparent bias toward inverse agonists among the docking hits, have implications for structure-based approaches against GPCRs that recognize small org. mols.
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Sabio, M.; Jones, K.; Topiol, S. Use of the X-ray structure of the beta(2)-adrenergic receptor for drug discovery. Part 2: Identification of active compounds Bioorg. Med. Chem. Lett. 2008, 18, 5391– 5395
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de Graaf, C.; Rognan, D. Selective structure-based virtual screening for full and partial agonists of the beta 2 adrenergic receptor J. Med. Chem. 2008, 51, 4978– 4985
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Katritch, V.; Reynolds, K. A.; Cherezov, V.; Hanson, M. A.; Roth, C. B.; Yeager, M.; Abagyan, R. Analysis of full and partial agonists binding to beta(2)-adrenergic receptor suggests a role of transmembrane helix V in agonist-specific conformational changes J. Mol. Recognit. 2009, 22, 307– 318
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Analysis of full and partial agonists binding to β2-adrenergic receptor suggests a role of transmembrane helix V in agonist-specific conformational changes
Katritch, Vsevolod; Reynolds, Kimberly A.; Cherezov, Vadim; Hanson, Michael A.; Roth, Christopher B.; Yeager, Mark; Abagyan, Ruben
Journal of Molecular Recognition (2009), 22 (4), 307-318CODEN: JMORE4; ISSN:0952-3499. (John Wiley & Sons Ltd.)
The 2.4 Å crystal structure of the β2-adrenergic receptor (β2AR) in complex with the high-affinity inverse agonist (-)-carazolol provides a detailed structural framework for the anal. of ligand recognition by adrenergic receptors. Insights into agonist binding and the corresponding conformational changes triggering G-protein coupled receptor (GPCR) activation mechanism are of special interest. While the carazolol pocket captured in the β2AR crystal structure accommodates (-)-isoproterenol and other agonists without steric clashes, a finite movement of the flexible extracellular part of TM-V helix (TM-Ve) obtained by receptor optimization in the presence of docked ligand can further improve the calcd. binding affinities for agonist compds. Tilting of TM-Ve towards the receptor axis provides a more complete description of polar receptor-ligand interactions for full and partial agonists, by enabling optimal engagement of agonists with two exptl. identified anchor sites, formed by Asp 113/Asn 312 and Ser 203/Ser 204/Ser 207 side chains. Further, receptor models incorporating a flexible TM-V backbone allow reliable prediction of binding affinities for a set of diverse ligands, suggesting potential utility of this approach to design of effective and subtype-specific agonists for adrenergic receptors. Systematic differences in capacity of partial, full and inverse agonists to induce TM-V helix tilt in the β2AR model suggest potential role of TM-V as a conformational "rheostat" involved in the whole spectrum of β2AR responses to small mol. signals.
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Reynolds, K. A.; Katritch, V.; Abagyan, R. Identifying conformational changes of the beta(2) adrenoceptor that enable accurate prediction of ligand/receptor interactions and screening for GPCR modulators J. Comput.-Aided Mol. Des. 2009, 23, 273– 288
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Identifying conformational changes of the β2 adrenoceptor that enable accurate prediction of ligand/receptor interactions and screening for GPCR modulators
Reynolds, Kimberly A.; Katritch, Vsevolod; Abagyan, Ruben
Journal of Computer-Aided Molecular Design (2009), 23 (5), 273-288CODEN: JCADEQ; ISSN:0920-654X. (Springer)
The new β2 Adrenoceptor (β2AR) crystal structures provide a high-resoln. snapshot of receptor interactions with two particular partial inverse agonists, (-)-carazolol and timolol. However, both exptl. and computational studies of GPCR structure are significantly complicated by the existence of multiple conformational states coupled to ligand type and receptor activity. Agonists and antagonists induce or stabilize distinct changes in receptor structure that mediate a range of pharmacol. activities. In this work, the authors (1) established that the existing β2AR crystallog. conformers can be extended to describe ligand/receptor interactions for addnl. antagonist types, (2) generated agonist-bound receptor conformations, and (3) validated these models for agonist and antagonist virtual ligand screening (VLS). Using a ligand directed refinement protocol, the authors derived a single agonist-bound receptor conformation that selectively retrieved a diverse set of full and partial β2AR agonists in VLS trials. Addnl., the impact of extracellular loop two conformation on VLS was assessed by docking studies with rhodopsin-based β2AR homol. models, and loop-deleted receptor models. A general strategy for constructing and selecting agonist-bound receptor pocket conformations is presented, which may prove broadly useful in creating agonist and antagonist bound models for other GPCRs.
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Kuntz, I. D.; Blaney, J. M.; Oatley, S. J.; Langridge, R.; Ferrin, T. E. A geometric approach to macromolecule−ligand interactions J. Mol. Biol. 1982, 161, 269– 288
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A geometric approach to macromolecule-ligand interactions
Kuntz, Irwin D.; Blaney, Jeffrey M.; Oatley, Stuart J.; Langridge, Robert; Ferrin, Thomas E.
Journal of Molecular Biology (1982), 161 (2), 269-88CODEN: JMOBAK; ISSN:0022-2836.
A method is described to explore geometrically feasible alignments of ligands and receptors of known structure. Algorithms are presented that examine many binding geometries and evaluate them in terms of steric overlap. The procedure uses specific mol. conformations. A method is included for finding putative binding sites on a macromol. surface. Results are reported for heme-myoglobin interaction and the binding of thyroid hormone analogs to prealbumin. In each case, the program finds structures within 1 Å of the x-ray results and also finds distinctly different geometries that provide good steric fits. The approach seems well-suited for generating conformations for energy refinement programs and interactive computer graphics routines.
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Shoichet, B. K.; Kuntz, I. D. Matching chemistry and shape in molecular docking Protein Eng. 1993, 6, 723– 732
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Matching chemistry and shape in molecular docking
Shoichet, Brian K.; Kuntz, Irwin D.
Protein Engineering (1993), 6 (7), 723-32CODEN: PRENE9; ISSN:0269-2139.
The authors have added a chem. filter to the ligand placement algorithm of the mol. docking program DOCK. DOCK places ligands in receptors using local shape features. Here the authors label these shape features by chem. type and insist on complementary matches. The authors find fewer phys. unrealistic complexes without reducing the no. of complexes resembling the known ligand-receptor configurations. Approx. 10-fold fewer complexes are calcd. and the new algorithm is correspondingly 10-fold faster than the previous shape-only matching. The authors tested the new algorithm's ability to reproduce three known ligand-receptor complexes: methotrexate in dihydrofolate reductase, deoxyuridine monophosphate in thymidylate synthase and pancreatic trypsin inhibitor in trypsin. The program found configurations within 1 Å of the crystallog. mode, with fewer nonnative solns. compared with shape-only matching. The authors also tested the program's ability to retrieve known inhibitors of thymidylate synthase and dihydrofolate reductase by screening mol. databases against the enzyme structures. Both algorithms retrieved many known inhibitors preferentially to other compds. in the database. The chem. matching algorithm generally ranks known inhibitors better than does matching based on shape alone.
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Nicholls, A.; Honig, B. A rapid finite-difference algorithm, utilizing successive over-relaxation to solve the Poisson−Boltzmann equation J. Comput. Chem. 1991, 12, 435– 445
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Weiner, S. J.; Kollman, P. A.; Case, D. A.; Singh, U. C.; Ghio, C.; Alagona, G.; Profeta, S.; Weiner, P. A new force-field for molecular mechanical simulation of nucleic-acids and proteins J. Am. Chem. Soc. 1984, 106, 765– 784
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A new force field for molecular mechanical simulation of nucleic acids and proteins
Weiner, Scott J.; Kollman, Peter A.; Case, David A.; Singh, U. Chandra; Ghio, Caterina; Alagona, Guliano; Profeta, Salvatore, Jr.; Weiner, Paul
Journal of the American Chemical Society (1984), 106 (3), 765-84CODEN: JACSAT; ISSN:0002-7863.
A force field was developed for simulation of nucleic acids and proteins. The approach began by obtaining equil. bond lengths and angles from microwave, neutron diffraction, and prior mol. mech. calcns., torsional consts. from microwave, NMR, and mol. mech. studies, nonbonded parameters from crystal packing calcns., and at. charges from the fit of a partial charge model to electrostatic potentials calcd. by ab initio quantum mech. theory. The parameters then were refined with mol. mech. studies on the structures and energies of model compds. For nucleic acids, Me Et ether, THF, deoxyadenosine, di-Me phosphate, 9-methylguanine-1-methylcytosine H-bonded complex, 9-methyladenine-1-methylthymine H-bonded complex, and 1,3-dimethyluracil base-stacked dimer were studied. Bond, angle, torsional, nonbonded, and H-bond parameters were varied to optimize the agreement between calcd. and exptl. values for sugar pucker energies and structures, vibrational frequencies of di-Me phosphate and THF, and energies for base pairing and base stacking. For proteins, Φ,ψ maps of glycyl and alanyl dipeptides, H-bonding interactions involving the various protein polar groups, and energy refinement calcns. on insulin were considered. Unlike the models for H bonding involving N and O electron donors, an adequate description of S-H bonding required explicit inclusion of lone pairs.
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Babaoglu, K.; Simeonov, A.; Lrwin, J. J.; Nelson, M. E.; Feng, B.; Thomas, C. J.; Cancian, L.; Costi, M. P.; Maltby, D. A.; Jadhav, A.; Inglese, J.; Austin, C. P.; Shoichet, B. K. Comprehensive mechanistic analysis of hits from high-throughput and docking screens against beta-lactamase J. Med. Chem. 2008, 51, 2502– 2511
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Comprehensive Mechanistic Analysis of Hits from High-Throughput and Docking Screens against β-Lactamase
Babaoglu, Kerim; Simeonov, Anton; Irwin, John J.; Nelson, Michael E.; Feng, Brian; Thomas, Craig J.; Cancian, Laura; Costi, M. Paola; Maltby, David A.; Jadhav, Ajit; Inglese, James; Austin, Christopher P.; Shoichet, Brian K.
Journal of Medicinal Chemistry (2008), 51 (8), 2502-2511CODEN: JMCMAR; ISSN:0022-2623. (American Chemical Society)
High-throughput screening (HTS) is widely used in drug discovery. Esp. for screens of unbiased libraries, false positives can dominate "hit lists"; their origins are much debated. Here we det. the mechanism of every active hit from a screen of 70,563 unbiased mols. against β-lactamase using quant. HTS (qHTS). Of the 1274 initial inhibitors, 95% were detergent-sensitive and were classified as aggregators. Among the 70 remaining were 25 potent, covalent-acting β-lactams. Mass spectra, counter-screens, and crystallog. identified 12 as promiscuous covalent inhibitors. The remaining 33 were either aggregators or irreproducible. No specific reversible inhibitors were found. We turned to mol. docking to prioritize mols. from the same library for testing at higher concns. Of 16 tested, 2 were modest inhibitors. Subsequent X-ray structures corresponded to the docking prediction. Analog synthesis improved affinity to 8 μM. These results suggest that it may be the phys. behavior of org. mols., not their reactivity, that accounts for most screening artifacts. Structure-based methods may prioritize weak-but-novel chemotypes in unbiased library screens.
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Powers, R. A.; Morandi, F.; Shoichet, B. K. Structure-based discovery of a novel, noncovalent inhibitor of AmpC beta-lactamase Structure 2002, 10, 1013– 1023
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Structure-Based Discovery of a Novel, Noncovalent Inhibitor of AmpC β-Lactamase
Powers, Rachel A.; Morandi, Federica; Shoichet, Brian K.
Structure (Cambridge, MA, United States) (2002), 10 (7), 1013-1023CODEN: STRUE6; ISSN:0969-2126. (Cell Press)
β-Lactamases are the most widespread resistance mechanisms to β-lactam antibiotics, and there is a pressing need for novel, non-β-lactam drugs. A database of over 200,000 compds. was docked to the active site of AmpC β-lactamase to identify potential inhibitors. Fifty-six compds. were tested, and three had Ki values of 650 μM or better. The best of these, 3-[(4-chloroanilino)sulfonyl]thiophene-2-carboxylic acid, was a competitive noncovalent inhibitor (Ki = 26 μM), which also reversed resistance to β-lactams in bacteria expressing AmpC. The structure of AmpC in complex with this compd. was detd. by x-ray crystallog. to 1.94 A and reveals that the inhibitor interacts with key active-site residues in sites targeted in the docking calcn. Indeed, the exptl. detd. conformation of the inhibitor closely resembles the prediction. The structure of the enzyme-inhibitor complex presents an opportunity to improve binding affinity in a novel series of inhibitors discovered by structure-based methods.
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Meng, E. C.; Shoichet, B. K.; Kuntz, I. D. Automated docking with grid-based energy evaluation J. Comput. Chem. 1992, 13, 505– 524
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Automated docking with grid-based energy evaluation
Meng, Elaine C.; Shoichet, Brian K.; Kuntz, Irwin D.
Journal of Computational Chemistry (1992), 13 (4), 505-24CODEN: JCCHDD; ISSN:0192-8651.
The ability to generate feasible binding orientations of a small mol. within a site of known structure is important for ligand design. The authors present a method that combines a rapid, geometric docking algorithm with the evaluation of mol. mechanics interaction energies. The computational costs of evaluation are minimal because the authors precalc. the receptor-dependent terms in the potential function at points on a three-dimensional grid. In four test cases where the components of crystallog. detd. complexes are redocked, the "force field" score correctly identifies the family of orientations closest to the exptl. binding geometry. Scoring functions that consider only steric factors or only electrostatic factors are less successful. The force field function will play an important role in efforts to search databases for potential lead compds.
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Shoichet, B. K.; Leach, A. R.; Kuntz, I. D. Ligand solvation in molecular docking Proteins: Struct., Funct., Genet. 1999, 34, 4– 16
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Wei, B. Q. Q.; Baase, W. A.; Weaver, L. H.; Matthews, B. W.; Shoichet, B. K. A model binding site for testing scoring functions in molecular docking J. Mol. Biol. 2002, 322, 339– 355
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A Model Binding Site for Testing Scoring Functions in Molecular Docking
Wei, Binqing Q.; Baase, Walter A.; Weaver, Larry H.; Matthews, Brian W.; Shoichet, Brian K.
Journal of Molecular Biology (2002), 322 (2), 339-355CODEN: JMOBAK; ISSN:0022-2836. (Elsevier Science Ltd.)
Prediction of interaction energies between ligands and their receptors remains a major challenge for structure-based inhibitor discovery. Much effort has been devoted to developing scoring schemes that can successfully rank the affinities of a diverse set of possible ligands to a binding site for which the structure is known. To test these scoring functions, well-characterized exptl. systems can be very useful. Here, mutation-created binding sites in T4 lysozyme were used to investigate how the quality of at. charges and solvation energies affects mol. docking. At. charges and solvation energies were calcd. for 172,118 mols. in the Available Chems. Directory using a semi-empirical quantum mech. approach by the program AMSOL. The database was first screened against the apolar cavity site created by the mutation Leu99Ala (L99A). Compared to the electronegativity-based charges that are widely used, the new charges and desolvation energies improved ranking of known apolar ligands, and better distinguished them from more polar isosteres that are not obsd. to bind. To investigate whether the new charges had predictive value, the non-polar residue Met102, which forms part of the binding site, was changed to the polar residue glutamine. The structure of the resulting Leu99 Ala and Met102 Gln double mutant of T4 lysozyme (L99A/M102Q) was detd. and the docking calcn. was repeated for the new site. Seven representative polar mols. that preferentially docked to the polar vs. the apolar binding site were tested exptl. All seven bind to the polar cavity (L99A/M102Q) but do not detectably bind to the apolar cavity (L99A). Five ligand-bound structures of L99A/M102Q were detd. by X-ray crystallog. Docking predictions corresponded to the crystallog. results to within 0.4 A RMSD. Improved treatment of partial at. charges and desolvation energies in database docking appears feasible and leads to better distinction of true ligands. Simple model binding sites, such as L99A and its more polar variants, may find broad use in the development and testing of docking algorithms.
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Irwin, J. J.; Shoichet, B. K. ZINC—a free database of commercially available compounds for virtual screening J. Chem. Inf. Model. 2005, 45, 177– 182
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ZINC - A Free Database of Commercially Available Compounds for Virtual Screening
Irwin, John J.; Shoichet, Brian K.
Journal of Chemical Information and Computer Sciences (2005), 45 (1), 177-182CODEN: JCISD8; ISSN:0095-2338. (American Chemical Society)
A crit. barrier to entry into structure-based virtual screening is the lack of a suitable, easy to access database of purchasable compds. We have therefore prepd. a library of 727 842 mols., each with 3D structure, using catalogs of compds. from vendors (the size of this library continues to grow). The mols. have been assigned biol. relevant protonation states and are annotated with properties such as mol. wt., calcd. LogP, and no. of rotatable bonds. Each mol. in the library contains vendor and purchasing information and is ready for docking using a no. of popular docking programs. Within certain limits, the mols. are prepd. in multiple protonation states and multiple tautomeric forms. In one format, multiple conformations are available for the mols. This database is available for free download (http://zinc.docking.org) in several common file formats including SMILES, mol2, 3D SDF, and DOCK flexibase format. A Web-based query tool incorporating a mol. drawing interface enables the database to be searched and browsed and subsets to be created. Users can process their own mols. by uploading them to a server. Our hope is that this database will bring virtual screening libraries to a wide community of structural biologists and medicinal chemists.
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Bostrom, J.; Greenwood, J. R.; Gottfries, J. Assessing the performance of OMEGA with respect to retrieving bioactive conformations J. Mol. Graphics Modell. 2003, 21, 449– 462
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Assessing the performance of OMEGA with respect to retrieving bioactive conformations
Bostrom, Jonas; Greenwood, Jeremy R.; Gottfries, Johan
Journal of Molecular Graphics & Modelling (2003), 21 (5), 449-462CODEN: JMGMFI; ISSN:1093-3263. (Elsevier Science Inc.)
OMEGA is a rule-based program which rapidly generates conformational ensembles of small mols. We have varied the parameters which control the nature of the ensembles generated by OMEGA in a statistical fashion (D-optimal) with the aim of increasing the probability of generating bioactive conformations. Thirty-six drug-like ligands from different ligand-protein complexes detd. by high-resoln. (≤ 2.0 Å) x-ray crystallog. have been analyzed. Statistically significant models (Q2 ≥ 0.75) confirm that one can increase the performance of OMEGA by modifying the parameters. Twenty-eight of the bioactive conformations were retrieved when using a low-energy cut-off (5 kcal/mol), a low RMSD value (0.6 Å) for duplicate removal, and a max. of 1000 output conformations. All of those that were not retrieved had eight or more rotatable bonds. The duplicate removal parameter was found to have the largest impact on retrieval of bioactive conformations, and the max. no. of conformations also affected the results considerably. The input conformation was found to influence the results largely because certain bond angles can prevent the bioactive conformation from being generated as a low-energy conformation. Pre-optimizing the input structures with MMFF94s improved the results significantly. We also investigated the performance of OMEGA in connection with database searching. The shape-matching program Rapid Overlay of Chem. Structures (ROCS) was used as search tool. Two multi-conformational databases were built from the MDDR database plus the 36 compds.; one large (max. 1000 conformations/mol) and one small (max. 100 conformations/mol). Both databases provided satisfactory results in terms of retrieval. ROCS was able to rank 35 out of 36 x-ray structures among the top 500 hits from the large database.
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Chambers, C. C.; Hawkins, G. D.; Cramer, C. J.; Truhlar, D. G. Model for aqueous solvation based on class IV atomic charges and first solvation shell effects J. Phys. Chem. 1996, 100, 16385– 16398
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Model for Aqueous Solvation Based on Class IV Atomic Charges and First Solvation Shell Effects
Chambers, Candee C.; Cramer, Christopher J.; Truhlar, Donald G.
Journal of Physical Chemistry (1996), 100 (40), 16385-16398CODEN: JPCHAX; ISSN:0022-3654. (American Chemical Society)
A new set of geometry-based functional forms is presented for parameterizing effective Coulomb radii and at. surface tensions of org. solutes in water. In particular, the radii and surface tensions depend in some cases on distances to nearby atoms. Combining the surface tensions with electrostatic effects included in a Fock operator by the generalized Born model enables one to calc. free energies of solvation, and exptl. free energies of solvation are used to parametrize the theory for water. At. charges are obtained by both the AM1-CM1A and PM3-CM1P class IV charge models, which yield similar results, and hence the same radii and surface tensions are used with both charge models. The authors considered 215 neutral solutes contg. H, C, N, O, F, S, Cl, Br, and I and encompassing a very wide variety of org. functional groups, and a mean unsigned error in the free energy of hydration of 0.50 kcal/mol using CM1A charges and 0.48 kcal/mol using CM1P charges was obtained. The predicted solvation energies for 12 cationic and 22 anionic solutes have mean unsigned deviations from expt. of 4.6 and 4.8 kcal/mol for models based on AM1 and PM3, resp.
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Li, J. B.; Zhu, T. H.; Cramer, C. J.; Truhlar, D. G. New class IV charge model for extracting accurate partial charges from wave functions J. Phys. Chem. A 1998, 102, 1820– 1831
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New Class IV Charge Model for Extracting Accurate Partial Charges from Wave Functions
Li, Jiabo; Zhu, Tianhai; Cramer, Christopher J.; Truhlar, Donald G.
Journal of Physical Chemistry A (1998), 102 (10), 1820-1831CODEN: JPCAFH; ISSN:1089-5639. (American Chemical Society)
We propose a new formalism, charge model 2 (CM2), to obtain accurate partial at. charges from a population anal. of wave functions by a parametrized mapping procedure, so that the resulting charges reproduce highly accurate charge-dependent observables. The new method, which produces class IV charges, is illustrated by developing CM2 mappings of Lowdin charges obtained from semiempirical and ab initio Hartree-Fock theory and d. functional theory, in particular AM1, PM3, HF/MIDI!, HF/6-31G*, HF/6-31+G*, BPW91/MIDI!, BPW91/6-31G*, B3LYP/MIDI!, and BPW91/DZVP calcns. The CM2 partial charges reproduce exptl. dipole moments with root-mean-square errors that are typically a factor of 7 better than dipole moments computed from Mulliken population anal., a factor of 3 better than dipole moments computed by Lowdin anal., and even a factor of 2 better than dipole moments computed from the continuous electron d. At the HF/6-31G* and B3LYP/MIDI! levels, the new charge model yields root-mean-square errors of 0.19 and 0.18 D, resp., for the dipole moments of a set of 211 polar mols. contg. a diverse range of structures and org. functional groups and the elements H, C, N, O, F, Si, P, S, Cl, Br, and I. A comparison shows that the new charge model predicts dipole moments more accurately than MP2/cc-pVDZ calcns., which are considerably more expensive. The quality of the results is similarly good for electrostatic potentials and for the other parametrizations as well.
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An all atom force field for simulations of proteins and nucleic acids
Weiner, Scott J.; Kollman, Peter A.; Nguyen, Dzung T.; Case, David A.
Journal of Computational Chemistry (1986), 7 (2), 230-52CODEN: JCCHDD; ISSN:0192-8651.
An all-atom potential energy function for the simulation of proteins and nucleic acids is presented. This work is an extension of the CH united atom function recently presented by S. J. Weiner et al. (1984). The parameters of this function are based on calcns. on ethane, propane, n-butane, di-Me ether, Me Et ether, THF, imidazole, indole, deoxyadenosine, base-paired dinucleoside phosphates, adenine, guanine, uracil, cytosine, thymine, insulin, and myoglobin. These parameters were also used to carry out the 1st general vibrational anal. of all 5 nucleic acid bases with a mol. mechanics potential approach.
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Keiser, M. J.; Roth, B. L.; Armbruster, B. N.; Ernsberger, P.; Irwin, J. J.; Shoichet, B. K. Relating protein pharmacology by ligand chemistry Nat. Biotechnol. 2007, 25, 197– 206
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Relating protein pharmacology by ligand chemistry
Keiser, Michael J.; Roth, Bryan L.; Armbruster, Blaine N.; Ernsberger, Paul; Irwin, John J.; Shoichet, Brian K.
Nature Biotechnology (2007), 25 (2), 197-206CODEN: NABIF9; ISSN:1087-0156. (Nature Publishing Group)
The identification of protein function based on biol. information is an area of intense research. Here the authors consider a complementary technique that quant. groups and relates proteins based on the chem. similarity of their ligands. The authors began with 65,000 ligands annotated into sets for hundreds of drug targets. The similarity score between each set was calcd. using ligand topol. A statistical model was developed to rank the significance of the resulting similarity scores, which are expressed as a min. spanning tree to map the sets together. Although these maps are connected solely by chem. similarity, biol. sensible clusters nevertheless emerged. Links among unexpected targets also emerged, among them that methadone, emetine and loperamide (Imodium) may antagonize muscarinic M3, α2 adrenergic and neurokinin NK2 receptors, resp. These predictions were subsequently confirmed exptl. Relating receptors by ligand chem. organizes biol. to reveal unexpected relationships that may be assayed using the ligands themselves.
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Tondi, D.; Morandi, F.; Bonnet, R.; Costi, M. P.; Shoichet, B. K. Structure-based optimization of a non-beta-lactam lead results in inhibitors that do not up-regulate beta-lactamase expression in cell culture J. Am. Chem. Soc. 2005, 127, 4632– 4639
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Structure-Based Optimization of a Non-β-lactam Lead Results in Inhibitors That Do Not Up-Regulate β-Lactamase Expression in Cell Culture
Tondi, Donatella; Morandi, Federica; Bonnet, Richard; Costi, M. Paola; Shoichet, Brian K.
Journal of the American Chemical Society (2005), 127 (13), 4632-4639CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)
Bacterial expression of β-lactamases is the most widespread resistance mechanism to β-lactam antibiotics, such as penicillins and cephalosporins. There is a pressing need for novel, non-β-lactam inhibitors of these enzymes. One previously discovered novel inhibitor of the β-lactamase AmpC (I) has several favorable properties: it is chem. dissimilar to β-lactams and is a noncovalent, competitive inhibitor of the enzyme. However, at 26 μM its activity is modest. Using the x-ray structure of the AmpC/I complex as a template, 14 analogs were designed and synthesized. The most active of these, (II), had a Ki of 1 μM, 26-fold better than the lead. To understand the origins of this improved activity, the structures of AmpC in complex with compd. II and an analog were detd. by x-ray crystallog. to 1.97 and 1.96 Å, resp. II was active in cell culture, reversing resistance to the third generation cephalosporin ceftazidime in bacterial pathogens expressing AmpC. In contrast to β-lactam-based inhibitors clavulanate and cefoxitin, compd. II did not up-regulate β-lactamase expression in cell culture but simply inhibited the enzyme expressed by the resistant bacteria. Its escape from this resistance mechanism derives from its dissimilarity to β-lactam antibiotics.
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Jarvis, M. F.; Schulz, R.; Hutchison, A. J.; Do, U. H.; Sills, M. A.; Williams, M. [H-3] Cgs-21680, a selective A2 adenosine receptor agonist directly labels A2-receptors in rat-brain J. Pharmacol. Exp. Ther. 1989, 251, 888– 893
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[3H]CGS 21680, a selective A2 adenosine receptor agonist directly labels A2 receptors in rat brain
Jarvis, Michael F.; Schulz, Rainer; Hutchison, Alan J.; Do, Un Hoi; Sills, Matthew A.; Williams, Michael
Journal of Pharmacology and Experimental Therapeutics (1989), 251 (3), 888-93CODEN: JPETAB; ISSN:0022-3565.
Characterization of the adenosine A2 receptor has been limited due to the lack of available ligands which have high affinity and selectivity for this adenosine receptor subtype. In the present study, the binding of a highly A2-selective agonist radioligand, [3H]CGS 21680 (I) is described. [3H]CGS 21680 specific binding to rat striatal membranes was saturable, reversible, and dependent on protein concn. Satn. studies revealed that [3H]CGS 21680 bound with high affinity (Kd =15.5 nM) and limited capacity (apparent Bmax = 375 fmol/mg protein) to a single class of recognition sites. Ests. of ligand affinity (16 nM) detd. from assocn. and dissocn. kinetic expts. were in close agreement with the results from the satn. studies. [3H]CGS 21680 binding was greatest in striatal membranes with negligible specific binding obtained in rat cortical membranes. Adenosine agonists ligands competed for the binding of 5 nM [3H]CGS 21680 to striatal membranes with the following order of activity; CGS 21680 = 5'-N-ethylcarboxamidoadenosine > 2-phenylaminoadenosine (CV-1808) ; 5'-N-methylcarboxamidoadenosine = 2-chloroadenosine > R-phenylisopropyladenosine > N6-cyclohexyladenosine > N6-cyclopentyltheophylline > S-phenylisopropyladenosine. The nonxanthine adenosine antagonist, CGS 15943A, was the most active compd. in inhibiting the binding of [3H]CGS 21680. Other adenosine antagonists inhibited binding in the following order; xanthine amine congener = (1,3-dipropyl-8-(2-amino-4-chloro)phenylxanthine > 1,3-dipropyl-8-cyclopentylxanthine > 1,3-diethyl-8-phenylxanthine > 8-phenyltheophylline > 8-cyclopentyltheophylline = xanthine carboxylic acid congener > 8-parasulfophenyltheophylline > theophylline > caffeine. The pharmacol. profile of both adenosine agonist and antagonist compds. to compete for the binding of [3H]CGS 21680 was consistent with a selective interaction at the high affinity adenosine A2 receptor. A high pos. correlation was obsd. between the pharmacol. profile of adenosine ligands to inhibit the binding of [3H]CGS 21680 and the selective binding of [3H]NECA (+50 nM CPA) to high affinity A2 receptors. However, some differences between these assays were found for compds. which have moderate affinity and nonselective actions at both the A1 and A2 adenosine receptor subtypes. Unlike data obtained with nonselective adenosine ligands, the present results indicate that [3H]CGS 21680 directly labels the high affinity A2 receptor in rat brain without the need to block binding activity at the A1 receptor. The high degree of selectivity (>170-fold) and high affinity of [3H]CGS 21680 make this the current ligand of choice for the in vitro characterization of high affinity A2 receptors.
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Klotz, K. N.; Lohse, M. J.; Schwabe, U.; Cristalli, G.; Vittori, S.; Grifantini, M. 2-Chloro-N-6-[H-3]cyclopentyladenosine ([H-3]Ccpa), a high-affinity agonist radioligand for A1 adenosine receptors Naunyn-Schmiedeberg's Arch. Pharmacol. 1989, 340, 679– 683
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2-Chloro-N6-[3H]cyclopentyladenosine ([3H]CPPA) - a high affinity agonist radioligand for A1 adenosine receptors
Klotz, Karl Norbert; Lohse, Martin J.; Schwabe, Ulrich; Cristalli, Gloria; Vittori, Sauro; Grifantini, Mario
Naunyn-Schmiedeberg's Archives of Pharmacology (1989), 340 (6), 679-83CODEN: NSAPCC; ISSN:0028-1298.
The tritiated analog of 2-chloro-N6-cyclopentyladenosine (CCPA) (I), an adenosine deriv. with subnanomolar affinity and a 10,000-fold selectivity for A1 adenosine receptors, has been examd. as a new agonist radioligand. [3H]CCPA was prepd. with a specific radioactivity of 1.58 TBq/mmol (43 Ci/mmol) and bound in a reversible manner to A1 receptors from rat brain membranes with a high affinity KD value of 0.2 nmol/L. In the presence of GTP, a KDvalue of 13 nmol/L was detd. for the low affinity state for agonist binding. Competition of several adenosine receptor agonists and antagonists for [3H]CCPA binding to rat brain membranes confirmed binding to an A1 receptor. Solubilized A1 receptors bound [3H]CCPA with similar affinity for the high affinity state. At solubilized receptors a reduced assocn. rate was obsd. in the presence of MgCl2, as has been shown for the agonist [3H]N6-phenylisopropyladenosine ([3H]PIA). [3H]CCPA was also used for detection of A1 receptors in rat cardiomyocyte membranes, a tissue with a very low receptor d. Kd-Value of 0.4 nmol-L and a Bmax-value of 16 fmol-platelet membranes, no specific binding of [3H]CCPA was measured at concns. up to 400 nmol/L, indicating that A2 receptors did not bind [3H]CCPA. Based on the subnanomolar affinity and the high selectivity for A1 receptors, [3H]CCPA proved to be a useful agonist radioligand for characterization of A1 adenosine receptors also in tissues with very low receptor d.
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Several assays are described and detailed for the characterization and anal. of cAMP and adenylyl cyclase.
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A Specific Mechanism of Nonspecific Inhibition
McGovern, Susan L.; Helfand, Brian T.; Feng, Brian; Shoichet, Brian K.
Journal of Medicinal Chemistry (2003), 46 (20), 4265-4272CODEN: JMCMAR; ISSN:0022-2623. (American Chemical Society)
Promiscuous small mols. plague screening libraries and hit lists. Previous work has found that several nonspecific compds. form submicrometer aggregates, and it has been suggested that this aggregate species is responsible for the inhibition of many different enzymes. It is not understood how aggregates inhibit their targets. To address this question, biophys., kinetic, and microscopy methods were used to study the interaction of promiscuous, aggregate-forming inhibitors with model proteins. By use of centrifugation and gel electrophoresis, aggregates and protein were found to directly interact. This is consistent with a subsequent observation from confocal fluorescence microscopy that aggregates conc. green fluorescent protein. β-Lactamase mutants with increased or decreased thermodn. stability relative to wild-type enzyme were equally inhibited by an aggregate-forming compd., suggesting that denaturation by unfolding was not the primary mechanism of interaction. Instead, visualization by electron microscopy revealed that enzyme assocs. with the surface of inhibitor aggregates. This assocn. could be reversed or prevented by the addn. of Triton X-100. These observations suggest that the aggregates formed by promiscuous compds. reversibly sequester enzyme, resulting in apparent inhibition. They also suggest a simple method to identify or reverse the action of aggregate-based inhibitors, which appear to be widespread.
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Quantifying biogenic bias in screening libraries
Hert, Jerome; Irwin, John J.; Laggner, Christian; Keiser, Michael J.; Shoichet, Brian K.
Nature Chemical Biology (2009), 5 (7), 479-483CODEN: NCBABT; ISSN:1552-4450. (Nature Publishing Group)
In lead discovery, libraries of 106 mols. are screened for biol. activity. Given the over 1060 drug-like mols. thought possible, such screens might never succeed. The fact that they do, even occasionally, implies a biased selection of library mols. We have developed a method to quantify the bias in screening libraries toward biogenic mols. With this approach, we consider what is missing from screening libraries and how they can be optimized.
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Katritch, V.; Jaakola, V. P.; Lane, J. R.; Lin, J.; Ijzerman, A. P.; Yeager, M.; Kufareva, I.; Stevens, R. C.; Abagyan, R. Structure-based discovery of novel chemotypes for adenosine A(2A) receptor antagonists J. Med. Chem. 2010, 53, 1799– 1809
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Structure-Based Discovery of Novel Chemotypes for Adenosine A2A Receptor Antagonists
Katritch, Vsevolod; Jaakola, Veli-Pekka; Lane, J. Robert; Lin, Judy; IJzerman, Adriaan P.; Yeager, Mark; Kufareva, Irina; Stevens, Raymond C.; Abagyan, Ruben
Journal of Medicinal Chemistry (2010), 53 (4), 1799-1809CODEN: JMCMAR; ISSN:0022-2623. (American Chemical Society)
The recent progress in crystallog. of G-protein coupled receptors opens an unprecedented venue for structure-based GPCR drug discovery. To test efficiency of the structure-based approach, we performed mol. docking and virtual ligand screening (VLS) of more than 4 million com. available "drug-like" and "lead-like" compds. against the A2AAR 2.6 Å resoln. crystal structure. Out of 56 high ranking compds. tested in A2AAR binding assays, 23 showed affinities under 10 μM, 11 of those had sub-μM affinities and two compds. had affinities under 60 nM. The identified hits represent at least 9 different chem. scaffolds and are characterized by very high ligand efficiency (0.3-0.5 kcal/mol per heavy atom). Significant A2AAR antagonist activities were confirmed for 10 out of 13 ligands tested in functional assays. High success rate, novelty, and diversity of the chem. scaffolds and strong ligand efficiency of the A2AAR antagonists identified in this study suggest practical applicability of receptor-based VLS in GPCR drug discovery.
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Abstract
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Chart 1
Chart 1. Structures of Known Agonists (1−3) and Antagonists (4−6) of the A_2A Adenosine Receptor
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Figure 1
Figure 1. Binding mode of the cocrystallized ligand 6 (A) and the predicted binding modes of the seven ligands discovered in the docking screen (B−H). The A_2A AR binding site is shown in white ribbons with the side chains of Glu169 and Asn253 in sticks. In (A) the cocrystallized ligand 6 is shown using orange carbon atoms. In (B−H), the crystallographic ligand is shown using blue lines and the docking poses for the ligands are depicted with orange carbon atoms. Black dotted lines indicate hydrogen bonds. The compounds are (B) 7, (C) 8, (D) 9, (E) 10, (F) 11, (G) 12, and (H) 13.
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Figure 2
Figure 2. Representative dose−response curves for displacement of binding of the radiolabeled A_2A AR agonist 3 by compounds 9, 10, and 11.
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Figure 3
Figure 3. Functional assay based on measuring the production of cAMP for 3 (control), a potent A_2A AR agonist, with or without 10 μM 9 or 11. The dose−response curve is shifted for both compounds, as expected in the case of competitive antagonistic inhibition. The % activation refers to production of cAMP normalized to the effect of 3 at 100 μM.
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  A review. For the past decade, the no. of mol. targets for approved drugs has been debated. Here, we reconcile apparently contradictory previous reports into a comprehensive survey, and propose a consensus no. of current drug targets for all classes of approved therapeutic drugs. One striking feature is the relatively const. historical rate of target innovation (the rate at which drugs against new targets are launched); however, the rate of developing drugs against new families is significantly lower. The recent approval of drugs that target protein kinases highlights two addnl. trends: an emerging realization of the importance of polypharmacol., and also the power of a gene-family-led approach in generating novel and important therapies.
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  Second extracellular loop, which in the β2-adrenergic receptor contains an unusual pair of disulfide bonds and an extra helix. This loop and the absence Heterotrimeric guanine nucleotide-binding protein (G protein)-coupled receptors constitute the largest family of eukaryotic signal transduction proteins that communicate across the membrane. We report the crystal structure of a human β2-adrenergic receptor-T4 lysozyme fusion protein bound to the partial inverse agonist carazolol at 2.4 angstrom resoln. The structure provides a high-resoln. view of a human G protein-coupled receptor bound to a diffusible ligand. Ligand-binding site accessibility is enabled by the second extracellular loop, which is held out of the binding cavity by a pair of closely spaced disulfide bridges and a short helical segment within the loop. Cholesterol, a necessary component for crystn., mediates an intriguing parallel assocn. of receptor mols. in the crystal lattice. Although the location of carazolol in the β2-adrenergic receptor is very similar to that of retinal in rhodopsin, structural differences in the ligand-binding site and other regions highlight the challenges in using rhodopsin as a template model for this large receptor family.
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  The 2.6 Angstrom Crystal Structure of a Human A2A Adenosine Receptor Bound to an Antagonist
  Jaakola, Veli-Pekka; Griffith, Mark T.; Hanson, Michael A.; Cherezov, Vadim; Chien, Ellen Y. T.; Lane, J. Robert; IJzerman, Adriaan P.; Stevens, Raymond C.
  Science (Washington, DC, United States) (2008), 322 (5905), 1211-1217CODEN: SCIEAS; ISSN:0036-8075. (American Association for the Advancement of Science)
  The adenosine class of heterotrimeric guanine nucleotide-binding protein (G protein)-coupled receptors (GPCRs) mediates the important role of extracellular adenosine in many physiol. processes and is antagonized by caffeine. The authors have detd. the crystal structure of the human A2A adenosine receptor, in complex with a high-affinity subtype-selective antagonist, ZM241385, to 2.6 angstrom resoln. Four disulfide bridges in the extracellular domain, combined with a subtle repacking of the transmembrane helixes relative to the adrenergic and rhodopsin receptor structures, define a pocket distinct from that of other structurally detd. GPCRs. The arrangement allows for the binding of the antagonist in an extended conformation, perpendicular to the membrane plane. The binding site highlights an integral role for the extracellular loops, together with the helical core, in ligand recognition by this class of GPCRs and suggests a role for ZM241385 in restricting the movement of a tryptophan residue important in the activation mechanism of the class A receptors.
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  The impact of GPCR structures on pharmacology and structure-based drug design
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  British Journal of Pharmacology (2010), 159 (5), 986-996CODEN: BJPCBM; ISSN:1476-5381. (Wiley-Blackwell)
  A review. After many years of effort, recent tech. breakthroughs have enabled the X-ray crystal structures of three G-protein-coupled receptors (GPCRs) (β1 and β2 adrenergic and adenosine A2a) to be solved in addn. to rhodopsin. GPCRs, like other membrane proteins, have lagged behind sol. drug targets such as kinases and proteases in the no. of structures available and the level of understanding of these targets and their interaction with drugs. The availability of increasing nos. of structures of GPCRs is set to greatly increase our understanding of some of the key issues in GPCR biol. In particular, what constitutes the different receptor conformations that are involved in signaling and the mol. changes which occur upon receptor activation. How future GPCR structures might alter our views on areas such as agonist-directed signaling and allosteric regulation as well as dimerization is discussed. Knowledge of crystal structures in complex with small mols. will enable techniques in drug discovery and design, which have previously only been applied to sol. targets, to now be used for GPCR targets. These methods include structure-based drug design, virtual screening and fragment screening. This review considers how these methods have been used to address problems in drug discovery for kinase and protease targets and therefore how such methods are likely to impact GPCR drug discovery in the future.
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  Progress in the pursuit of therapeutic Adenosine receptor antagonists
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  Medicinal Research Reviews (2006), 26 (2), 131-159CODEN: MRREDD; ISSN:0198-6325. (John Wiley & Sons, Inc.)
  A review. Ever since the discovery of the hypotensive and bradycardiac effects of adenosine, adenosine receptors continue to represent promising drug targets. First, this is due to the fact that the receptors are expressed in a large variety of tissues. In particular, the actions of adenosine (or methylxanthine antagonists) in the central nervous system, in the circulation, on immune cells, and on other tissues can be beneficial in certain disorders. Second, there exists a large no. of ligands, which have been generated by introducing several modifications in the structure of the lead compds. (adenosine and methylxanthine), some of them highly specific. Four adenosine receptor subtypes (A1, A2A, A2B, and A3) have been cloned and pharmacol. characterized, all of which are G protein-coupled receptors. Adenosine receptors can be distinguished according to their preferred mechanism of signal transduction: A1 and A3 receptors interact with pertussis toxin-sensitive G proteins of the Gi and Go family; the canonical signaling mechanism of the A2A and of the A2B receptors is stimulation of adenylyl cyclase via Gs proteins. In addn. to the coupling to adenylyl cyclase, all four subtypes may pos. couple to phospholipase C via different G protein subunits. The development of new ligands, in particular, potent and selective antagonists, for all subtypes of adenosine receptors has so far been directed by traditional medicinal chem. The availability of genetic information promises to facilitate understanding of the drug-receptor interaction leading to the rational design of a potentially therapeutically important class of drugs. Moreover, mol. modeling may further rationalize obsd. interactions between the receptors and their ligands. In this review, we will summarize the most relevant progress in developing new therapeutic adenosine receptor antagonists.
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  Adenosine receptors as therapeutic targets
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  A review. Adenosine receptors are major targets of caffeine, the most commonly consumed drug in the world. There is growing evidence that they could also be promising therapeutic targets in a wide range of conditions, including cerebral and cardiac ischemic diseases, sleep disorders, immune and inflammatory disorders and cancer. After more than three decades of medicinal chem. research, a considerable no. of selective agonists and antagonists of adenosine receptors have been discovered, and some have been clin. evaluated, although none has yet received regulatory approval. However, recent advances in the understanding of the roles of the various adenosine receptor subtypes, and in the development of selective and potent ligands, as discussed in this review, have brought the goal of therapeutic application of adenosine receptor modulators considerably closer.
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  Handbook of Experimental Pharmacology (2009), 193 (Adenosine Receptors in Health and Disease), 471-534CODEN: HEPHD2; ISSN:0171-2004. (Springer GmbH)
  A review. The adenosine receptors (ARs) in the nervous system act as a kind of "go-between" to regulate the release of neurotransmitters (this includes all known neurotransmitters) and the action of neuromodulators (e.g., neuropeptides, neurotrophic factors). Receptor-receptor interactions and AR-transporter interplay occur as part of the adenosine's attempt to control synaptic transmission. A2AARs are more abundant in the striatum and A1ARs in the hippocampus, but both receptors interfere with the efficiency and plasticity-regulated synaptic transmission in most brain areas. The omnipresence of adenosine and A2A and A1 ARs in all nervous system cells (neurons and glia), together with the intensive release of adenosine following insults, makes adenosine a kind of "maestro" of the tripartite synapse in the homeostatic coordination of the brain function. Under physiol. conditions, both A2A and A1 ARs play an important role in sleep and arousal, cognition, memory and learning, whereas under pathol. conditions (e.g., Parkinson's disease, Alzheimer's disease, amyotrophic lateral sclerosis, stroke, epilepsy, drug addiction, pain, schizophrenia, depression), ARs operate a time/circumstance window where in some circumstances A1AR agonists may predominate as early neuroprotectors, and in other circumstances A2AAR antagonists may alter the outcomes of some of the pathol. deficiencies. In some circumstances, and depending on the therapeutic window, the use of A2AAR agonists may be initially beneficial; however, at later time points, the use of A2AAR antagonists proved beneficial in several pathologies. Since selective ligands for A1 and A2A ARs are now entering clin. trials, the time has come to det. the role of these receptors in neurol. and psychiatric diseases and identify therapies that will alter the outcomes of these diseases, therefore providing a hopeful future for the patients who suffer from these diseases.
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  A review. Extracellular adenosine is produced in a coordinated manner from cells following cellular challenge or tissue injury. Once produced, it serves as an autocrine- and paracrine-signaling mol. through its interactions with seven-membrane-spanning G-protein-coupled adenosine receptors. These signaling pathways have widespread physiol. and pathophysiol. functions. Immune cells express adenosine receptors and respond to adenosine or adenosine agonists in diverse manners. Extensive in vitro and in vivo studies have identified potent anti-inflammatory functions for all of the adenosine receptors on many different inflammatory cells and in various inflammatory disease processes. In addn., specific proinflammatory functions have also been ascribed to adenosine receptor activation. The potent effects of adenosine signaling on the regulation of inflammation suggest that targeting specific adenosine receptor activation or inactivation using selective agonists and antagonists could have important therapeutic implications in numerous diseases. This review is designed to summarize the current status of adenosine receptor signaling in various inflammatory cells and in models of inflammation, with an emphasis on the advancement of adenosine-based therapeutics to treat inflammatory disorders.
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  A review. The development of potent and selective agonists and antagonists of adenosine receptors (ARs) has been a target of medicinal chem. research for several decades, and recently the US Food and Drug Administration has approved Lexiscan, an adenosine deriv. substituted at the 2 position, for use as a pharmacol. stress agent in radionuclide myocardial perfusion imaging. Currently, some other adenosine A2A receptor (A2AAR) agonists and antagonists are undergoing preclin. testing and clin. trials. While agonists are potent antiinflammatory agents also showing hypotensive effects, antagonists are being developed for the treatment of Parkinson's disease. However, since there are still major problems in this field, including side effects, low brain penetration (for the targeting of CNS diseases), short half-life, or lack of in vivo effects, the design and development of new AR ligands is a hot research topic. This review presents an update on the medicinal chem. of A2AAR agonists and antagonists, and stresses the strong need for more selective ligands at the human A2AAR subtype, in particular in the case of agonists.
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  Poucher, S. M.; Keddie, J. R.; Singh, P.; Stoggall, S. M.; Caulkett, P. W. R.; Jones, G.; Collis, M. G. The in-vitro pharmacology of Zm-241385, a potent, nonxanthine, a(2a) selective adenosine receptor antagonist Br. J. Pharmacol. 1995, 115, 1096– 1102
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  The in vitro pharmacology of ZM 241385, a potent, non-xanthine, A2a selective adenosine receptor antagonist
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  British Journal of Pharmacology (1995), 115 (6), 1096-102CODEN: BJPCBM; ISSN:0007-1188. (Macmillan Scientific & Medical Division)
  This paper describes the in vitro pharmacol. of ZM 241385 (4-(2-[7-amino-2-(2-furyl) [1,2,4]-triazolo[2,3-a][1,3,5]triazin-5-ylamino]ethyl)phenol), a novel non-xanthine adenosine receptor antagonist with selectivity for the A2 receptor subtype. ZM 241385 had high affinity for A2a receptors. In rat pheochromocytoma cell membranes, ZM 241385 displaced binding of tritiated 5'-N-ethylcarboxamidoadenosine (NECA) with a pIC50 of 9.52, (95% confidence limits, c.l., 9.02-10.02). In guinea-pig isolated Langendorff hearts, ZM 241385 antagonized vasodilation of the coronary bed produced by 2-chloroadenosine (2-CADO) and 2-[p-(2-carboxyethyl) phenylamino]-5'-N-ethylcarboxamidoadenosine (CGS21680) with pA2 values of 8.57 (c.l., 8.45-8.68) and 9.02 (c.l., 8.79-9.24) resp. ZM 241385 had low potency at A2b receptors and antagonized the relaxant effects of adenosine in the guinea-pig aorta with a pA2 of 7.06 (c.l., 6.92-7.19). ZM 241385 had a low affinity at A1 receptors. In rat cerebral cortex membranes it displayed tritiated R-phenylisopropyladenosine (R-PIA) with a pIC50 of 5.69 (c.l., 5.57-5.81). ZM 241385 antagonized the bradycardic action of 2-CADO in guinea-pig atria with a pA2 of 5.95 (c.l., 5.72-6.18). ZM 241385 had low affinity for A3 receptors. At cloned rat A3 receptors expressed in chinese hamster ovary cells, it displayed iodinated aminobenzyl-5'-N-methylcarboxamido adenosine (AB-MECA) with a pIC50 of 3.82 (c.l., 3.67-4.06). ZM 241385 had no significant addnl. pharmacol. effects on the isolated tissues used in these studies at concns. three orders of magnitude greater than those which block A2a receptors. At 10 μM it displayed only minor inhibition of the bradycardic effects in guinea-pig atria to some concns. of carbachol. At 10 μM, ZM 241385 had a small inhibitory effect on relaxant effects of isoprenaline in guinea-pig aorta but no effect on sodium nitrite-induced relaxation. ZM 241385 (100 μM) was without effect on phenylephrine-induced tone in guinea-pig aorta. ZM 241385 (10 μM) had no inhibitory effect on rat hepatocyte phosphodiesterase types I, II, III and IV but caused a small inhibition of the calcium calmodulin-activated type I enzyme. ZM 241385 is the most selective adenosine A2a receptor antagonist yet described and is therefore a useful tool for characterization of responses mediated by A2 adenosine receptors.
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  Jones, G.; Willett, P.; Glen, R. C.; Leach, A. R.; Taylor, R. Development and validation of a genetic algorithm for flexible docking J. Mol. Biol. 1997, 267, 727– 748
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  Development and validation of a genetic algorithm for flexible docking
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  Journal of Molecular Biology (1997), 267 (3), 727-748CODEN: JMOBAK; ISSN:0022-2836. (Academic)
  Prediction of small mol. binding modes to macromols. of known three-dimensional structure is a problem of paramount importance in rational drug design (the "docking" problem). We report the development and validation of the program GOLD (Genetic Optimization for Ligand Docking). GOLD is an automated ligand docking program that uses a genetic algorithm to explore the full range of ligand conformational flexibility with partial flexibility of the protein and satisfies the fundamental requirement that the ligand must displace loosely bound water on binding. Numerous enhancements and modifications have been applied to the original technique resulting in a substantial increase in the reliability and the applicability of the algorithm. The advanced algorithm has been tested on a dataset of 100 complexes extd. from the Brookhaven Protein Data Bank. When used to dock the ligand back into the binding site, GOLD achieved a 71% success rate in identifying the exptl. binding mode.
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  Kairys, V.; Fernandes, M. X.; Gilson, M. K. Screening drug-like compounds by docking to homology models: a systematic study J. Chem. Inf. Model. 2006, 46, 365– 379
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  Screening Drug-Like Compounds by Docking to Homology Models: A Systematic Study
  Kairys, Visvaldas; Fernandes, Miguel X.; Gilson, Michael K.
  Journal of Chemical Information and Modeling (2006), 46 (1), 365-379CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
  In the absence of an exptl. solved structure, a homol. model of a protein target can be used instead for virtual screening of drug candidates by docking and scoring. This approach poses a no. of questions regarding the choice of the template to use in constructing the model, the accuracy of the screening results, and the importance of allowing for protein flexibility. The present study addresses such questions with compd. screening calcns. for multiple homol. models of five drug targets. A central result is that docking to homol. models frequently yields enrichments of known ligands as good as that obtained by docking to a crystal structure of the actual target protein. Interestingly, however, std. measures of the similarity of the template used to build the homol. model to the targeted protein show little correlation with the effectiveness of the screening calcns., and docking to the template itself often is as successful as docking to the corresponding homol. model. Treating key side chains as mobile produces a modest improvement in the results. The reasons for these sometimes unexpected results, and their implications for future methodol. development, are discussed.
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  Lorber, D. M.; Shoichet, B. K. Flexible ligand docking using conformational ensembles Protein Sci. 1998, 7, 938– 950
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  Flexible ligand docking using conformational ensembles
  Lorber, David M.; Shoichet, Brian K.
  Protein Science (1998), 7 (4), 938-950CODEN: PRCIEI; ISSN:0961-8368. (Cambridge University Press)
  Mol. docking algorithms suggest possible structures for mol. complexes. They are used to model biol. function and to discover potential ligands. A present challenge for docking algorithms is the treatment of mol. flexibility. Here, the rigid body program, DOCK, is modified to allow it to rapidly fit multiple conformations of ligands. Conformations of a given mol. are pre-calcd. in the same frame of ref., so that each conformer shares a common rigid fragment with all other conformations. The ligand conformers are then docked together, as an ensemble, into a receptor binding site. This takes advantage of the redundancy present in differing conformers of the same mol. The algorithm was tested using three org. ligand protein systems and two protein-protein systems. Both the bound and unbound conformations of the receptors were used. The ligand ensemble method found conformations that resembled those detd. in X-ray crystal structures (RMS values typically less than 1.5 Å). To test the method's usefulness for inhibitor discovery, multi-compd. and multi-conformer databases were screened for compds. known to bind to dihydrofolate reductase and compds. known to bind to thymidylate synthase. In both cases, known inhibitors and substrates were identified in conformations resembling those obsd. exptl. The ligand ensemble method was 100-fold faster than docking a single conformation at a time and was able to screen a database of over 34 million conformations from 117,000 mols. in one to four CPU days on a workstation.
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  Lorber, D. M.; Shoichet, B. K. Hierarchical docking of databases of multiple ligand conformations Curr. Top. Med. Chem. 2005, 5, 739– 749
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  Hierarchical docking of databases of multiple ligand conformations
  Lorber, David M.; Shoichet, Brian K.
  Current Topics in Medicinal Chemistry (Sharjah, United Arab Emirates) (2005), 5 (8), 739-749CODEN: CTMCCL; ISSN:1568-0266. (Bentham Science Publishers Ltd.)
  Ligand flexibility is an important problem in mol. docking and virtual screening. To address this challenge, we investigate a hierarchical pre-organization of multiple conformations of small mols. Such organization of pre-calcd. conformations removes the exploration of ligand conformational space from the docking calcn. and allows for concise representation of what can be thousands of conformations. The hierarchy also recognizes and prunes incompatible conformations early in the calcn., eliminating redundant calcns. of fit. We investigate the method by docking the MDL Drug Data Report (MDDR), an annotated database of 100,000 mols., into apo and holo forms of 7 unrelated targets. This annotated database allows us to track the ranking of tens to hundreds of annotated ligands in each of the docking systems. The binding sites and database are prepd. in an automated fashion in an attempt to remove some human bias from the calcns. Many thousands of explicit and implicit ligand conformations may be docked in calcns. not much longer than required for single conformer docking. As long as internal energies are not considered, recombination with the hierarchy is additive as the no. of degrees of freedom is increased. Mols. with even millions of conformations can be docked in a few minutes on a single desktop computer.
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  Zavodszky, M. I.; Kuhn, L. A. Side-chain flexibility in protein−ligand binding: the minimal rotation hypothesis Protein Sci. 2005, 14, 1104– 1114
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  Side-chain flexibility in protein-ligand binding: The minimal rotation hypothesis
  Zavodszky, Maria I.; Kuhn, Leslie A.
  Protein Science (2005), 14 (4), 1104-1114CODEN: PRCIEI; ISSN:0961-8368. (Cold Spring Harbor Laboratory Press)
  The goal of this work is to learn from nature about the magnitudes of side-chain motions that occur when proteins bind small org. mols. and model these motions to improve the prediction of protein-ligand complexes. Following anal. of protein side-chain motions upon ligand binding in 63 complexes, we tested the ability of the docking tool SLIDE to model these motions without being restricted to rotameric transitions or deciding which side chains should be considered as flexible. The model tested is that side-chain conformational changes involving more atoms or larger rotations are likely to be more costly and less prevalent than small motions due to energy barriers between rotamers and the potential of large motions to cause new steric clashes. Accordingly, SLIDE adjusts the protein and ligand side groups as little as necessary to achieve steric complementarity. We tested the hypothesis that small motions are sufficient to achieve good dockings using 63 ligands and the apo structures of 20 different proteins and compared SLIDE side-chain rotations to those exptl. obsd. None of these proteins undergoes major main-chain conformational change upon ligand binding, ensuring that side-chain flexibility modeling is not required to compensate for main-chain motions. Although more frugal in the no. of side-chain rotations performed, this model substantially mimics the exptl. obsd. motions. Most side chains do not shift to a new rotamer, and small motions are both necessary and sufficient to predict the correct binding orientation and most protein-ligand interactions for the 20 proteins analyzed.
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19. 19
  Kolb, P.; Rosenbaum, D. M.; Irwin, J. J.; Fung, J. J.; Kobilka, B. K.; Shoichet, B. K. Structure-based discovery of beta(2)-adrenergic receptor ligands Proc. Natl. Acad. Sci. U.S.A. 2009, 106, 6843– 6848
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  19
  Structure-based discovery of β2-adrenergic receptor ligands
  Kolb, Peter; Rosenbaum, Daniel M.; Irwin, John J.; Fung, Juan Jose; Kobilka, Brian K.; Shoichet, Brian K.
  Proceedings of the National Academy of Sciences of the United States of America (2009), 106 (16), 6843-6848CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)
  Aminergic G protein-coupled receptors (GPCRs) have been a major focus of pharmaceutical research for many years. Due partly to the lack of reliable receptor structures, drug discovery efforts have been largely ligand-based. The recently detd. X-ray structure of the β2-adrenergic receptor offers an opportunity to investigate the advantages and limitations inherent in a structure-based approach to ligand discovery against this and related GPCR targets. Approx. 1 million com. available, "lead-like" mols. were docked against the β2-adrenergic receptor structure. On testing of 25 high-ranking mols., 6 were active with binding affinities <4 μM, with the best mol. binding with a Ki of 9 nM (95% confidence interval 7-10 nM). Five of these mols. were inverse agonists. The high hit rate, the high affinity of the most potent mol., the discovery of unprecedented chemotypes among the new inhibitors, and the apparent bias toward inverse agonists among the docking hits, have implications for structure-based approaches against GPCRs that recognize small org. mols.
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20. 20
  Sabio, M.; Jones, K.; Topiol, S. Use of the X-ray structure of the beta(2)-adrenergic receptor for drug discovery. Part 2: Identification of active compounds Bioorg. Med. Chem. Lett. 2008, 18, 5391– 5395
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21. 21
  de Graaf, C.; Rognan, D. Selective structure-based virtual screening for full and partial agonists of the beta 2 adrenergic receptor J. Med. Chem. 2008, 51, 4978– 4985
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  There is no corresponding record for this reference.
22. 22
  Katritch, V.; Reynolds, K. A.; Cherezov, V.; Hanson, M. A.; Roth, C. B.; Yeager, M.; Abagyan, R. Analysis of full and partial agonists binding to beta(2)-adrenergic receptor suggests a role of transmembrane helix V in agonist-specific conformational changes J. Mol. Recognit. 2009, 22, 307– 318
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  22
  Analysis of full and partial agonists binding to β2-adrenergic receptor suggests a role of transmembrane helix V in agonist-specific conformational changes
  Katritch, Vsevolod; Reynolds, Kimberly A.; Cherezov, Vadim; Hanson, Michael A.; Roth, Christopher B.; Yeager, Mark; Abagyan, Ruben
  Journal of Molecular Recognition (2009), 22 (4), 307-318CODEN: JMORE4; ISSN:0952-3499. (John Wiley & Sons Ltd.)
  The 2.4 Å crystal structure of the β2-adrenergic receptor (β2AR) in complex with the high-affinity inverse agonist (-)-carazolol provides a detailed structural framework for the anal. of ligand recognition by adrenergic receptors. Insights into agonist binding and the corresponding conformational changes triggering G-protein coupled receptor (GPCR) activation mechanism are of special interest. While the carazolol pocket captured in the β2AR crystal structure accommodates (-)-isoproterenol and other agonists without steric clashes, a finite movement of the flexible extracellular part of TM-V helix (TM-Ve) obtained by receptor optimization in the presence of docked ligand can further improve the calcd. binding affinities for agonist compds. Tilting of TM-Ve towards the receptor axis provides a more complete description of polar receptor-ligand interactions for full and partial agonists, by enabling optimal engagement of agonists with two exptl. identified anchor sites, formed by Asp 113/Asn 312 and Ser 203/Ser 204/Ser 207 side chains. Further, receptor models incorporating a flexible TM-V backbone allow reliable prediction of binding affinities for a set of diverse ligands, suggesting potential utility of this approach to design of effective and subtype-specific agonists for adrenergic receptors. Systematic differences in capacity of partial, full and inverse agonists to induce TM-V helix tilt in the β2AR model suggest potential role of TM-V as a conformational "rheostat" involved in the whole spectrum of β2AR responses to small mol. signals.
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23. 23
  Reynolds, K. A.; Katritch, V.; Abagyan, R. Identifying conformational changes of the beta(2) adrenoceptor that enable accurate prediction of ligand/receptor interactions and screening for GPCR modulators J. Comput.-Aided Mol. Des. 2009, 23, 273– 288
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  23
  Identifying conformational changes of the β2 adrenoceptor that enable accurate prediction of ligand/receptor interactions and screening for GPCR modulators
  Reynolds, Kimberly A.; Katritch, Vsevolod; Abagyan, Ruben
  Journal of Computer-Aided Molecular Design (2009), 23 (5), 273-288CODEN: JCADEQ; ISSN:0920-654X. (Springer)
  The new β2 Adrenoceptor (β2AR) crystal structures provide a high-resoln. snapshot of receptor interactions with two particular partial inverse agonists, (-)-carazolol and timolol. However, both exptl. and computational studies of GPCR structure are significantly complicated by the existence of multiple conformational states coupled to ligand type and receptor activity. Agonists and antagonists induce or stabilize distinct changes in receptor structure that mediate a range of pharmacol. activities. In this work, the authors (1) established that the existing β2AR crystallog. conformers can be extended to describe ligand/receptor interactions for addnl. antagonist types, (2) generated agonist-bound receptor conformations, and (3) validated these models for agonist and antagonist virtual ligand screening (VLS). Using a ligand directed refinement protocol, the authors derived a single agonist-bound receptor conformation that selectively retrieved a diverse set of full and partial β2AR agonists in VLS trials. Addnl., the impact of extracellular loop two conformation on VLS was assessed by docking studies with rhodopsin-based β2AR homol. models, and loop-deleted receptor models. A general strategy for constructing and selecting agonist-bound receptor pocket conformations is presented, which may prove broadly useful in creating agonist and antagonist bound models for other GPCRs.
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24. 24
  Kuntz, I. D.; Blaney, J. M.; Oatley, S. J.; Langridge, R.; Ferrin, T. E. A geometric approach to macromolecule−ligand interactions J. Mol. Biol. 1982, 161, 269– 288
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  24
  A geometric approach to macromolecule-ligand interactions
  Kuntz, Irwin D.; Blaney, Jeffrey M.; Oatley, Stuart J.; Langridge, Robert; Ferrin, Thomas E.
  Journal of Molecular Biology (1982), 161 (2), 269-88CODEN: JMOBAK; ISSN:0022-2836.
  A method is described to explore geometrically feasible alignments of ligands and receptors of known structure. Algorithms are presented that examine many binding geometries and evaluate them in terms of steric overlap. The procedure uses specific mol. conformations. A method is included for finding putative binding sites on a macromol. surface. Results are reported for heme-myoglobin interaction and the binding of thyroid hormone analogs to prealbumin. In each case, the program finds structures within 1 Å of the x-ray results and also finds distinctly different geometries that provide good steric fits. The approach seems well-suited for generating conformations for energy refinement programs and interactive computer graphics routines.
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25. 25
  Shoichet, B. K.; Kuntz, I. D. Matching chemistry and shape in molecular docking Protein Eng. 1993, 6, 723– 732
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  25
  Matching chemistry and shape in molecular docking
  Shoichet, Brian K.; Kuntz, Irwin D.
  Protein Engineering (1993), 6 (7), 723-32CODEN: PRENE9; ISSN:0269-2139.
  The authors have added a chem. filter to the ligand placement algorithm of the mol. docking program DOCK. DOCK places ligands in receptors using local shape features. Here the authors label these shape features by chem. type and insist on complementary matches. The authors find fewer phys. unrealistic complexes without reducing the no. of complexes resembling the known ligand-receptor configurations. Approx. 10-fold fewer complexes are calcd. and the new algorithm is correspondingly 10-fold faster than the previous shape-only matching. The authors tested the new algorithm's ability to reproduce three known ligand-receptor complexes: methotrexate in dihydrofolate reductase, deoxyuridine monophosphate in thymidylate synthase and pancreatic trypsin inhibitor in trypsin. The program found configurations within 1 Å of the crystallog. mode, with fewer nonnative solns. compared with shape-only matching. The authors also tested the program's ability to retrieve known inhibitors of thymidylate synthase and dihydrofolate reductase by screening mol. databases against the enzyme structures. Both algorithms retrieved many known inhibitors preferentially to other compds. in the database. The chem. matching algorithm generally ranks known inhibitors better than does matching based on shape alone.
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26. 26
  Nicholls, A.; Honig, B. A rapid finite-difference algorithm, utilizing successive over-relaxation to solve the Poisson−Boltzmann equation J. Comput. Chem. 1991, 12, 435– 445
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27. 27
  Weiner, S. J.; Kollman, P. A.; Case, D. A.; Singh, U. C.; Ghio, C.; Alagona, G.; Profeta, S.; Weiner, P. A new force-field for molecular mechanical simulation of nucleic-acids and proteins J. Am. Chem. Soc. 1984, 106, 765– 784
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  27
  A new force field for molecular mechanical simulation of nucleic acids and proteins
  Weiner, Scott J.; Kollman, Peter A.; Case, David A.; Singh, U. Chandra; Ghio, Caterina; Alagona, Guliano; Profeta, Salvatore, Jr.; Weiner, Paul
  Journal of the American Chemical Society (1984), 106 (3), 765-84CODEN: JACSAT; ISSN:0002-7863.
  A force field was developed for simulation of nucleic acids and proteins. The approach began by obtaining equil. bond lengths and angles from microwave, neutron diffraction, and prior mol. mech. calcns., torsional consts. from microwave, NMR, and mol. mech. studies, nonbonded parameters from crystal packing calcns., and at. charges from the fit of a partial charge model to electrostatic potentials calcd. by ab initio quantum mech. theory. The parameters then were refined with mol. mech. studies on the structures and energies of model compds. For nucleic acids, Me Et ether, THF, deoxyadenosine, di-Me phosphate, 9-methylguanine-1-methylcytosine H-bonded complex, 9-methyladenine-1-methylthymine H-bonded complex, and 1,3-dimethyluracil base-stacked dimer were studied. Bond, angle, torsional, nonbonded, and H-bond parameters were varied to optimize the agreement between calcd. and exptl. values for sugar pucker energies and structures, vibrational frequencies of di-Me phosphate and THF, and energies for base pairing and base stacking. For proteins, Φ,ψ maps of glycyl and alanyl dipeptides, H-bonding interactions involving the various protein polar groups, and energy refinement calcns. on insulin were considered. Unlike the models for H bonding involving N and O electron donors, an adequate description of S-H bonding required explicit inclusion of lone pairs.
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28. 28
  Babaoglu, K.; Simeonov, A.; Lrwin, J. J.; Nelson, M. E.; Feng, B.; Thomas, C. J.; Cancian, L.; Costi, M. P.; Maltby, D. A.; Jadhav, A.; Inglese, J.; Austin, C. P.; Shoichet, B. K. Comprehensive mechanistic analysis of hits from high-throughput and docking screens against beta-lactamase J. Med. Chem. 2008, 51, 2502– 2511
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  28
  Comprehensive Mechanistic Analysis of Hits from High-Throughput and Docking Screens against β-Lactamase
  Babaoglu, Kerim; Simeonov, Anton; Irwin, John J.; Nelson, Michael E.; Feng, Brian; Thomas, Craig J.; Cancian, Laura; Costi, M. Paola; Maltby, David A.; Jadhav, Ajit; Inglese, James; Austin, Christopher P.; Shoichet, Brian K.
  Journal of Medicinal Chemistry (2008), 51 (8), 2502-2511CODEN: JMCMAR; ISSN:0022-2623. (American Chemical Society)
  High-throughput screening (HTS) is widely used in drug discovery. Esp. for screens of unbiased libraries, false positives can dominate "hit lists"; their origins are much debated. Here we det. the mechanism of every active hit from a screen of 70,563 unbiased mols. against β-lactamase using quant. HTS (qHTS). Of the 1274 initial inhibitors, 95% were detergent-sensitive and were classified as aggregators. Among the 70 remaining were 25 potent, covalent-acting β-lactams. Mass spectra, counter-screens, and crystallog. identified 12 as promiscuous covalent inhibitors. The remaining 33 were either aggregators or irreproducible. No specific reversible inhibitors were found. We turned to mol. docking to prioritize mols. from the same library for testing at higher concns. Of 16 tested, 2 were modest inhibitors. Subsequent X-ray structures corresponded to the docking prediction. Analog synthesis improved affinity to 8 μM. These results suggest that it may be the phys. behavior of org. mols., not their reactivity, that accounts for most screening artifacts. Structure-based methods may prioritize weak-but-novel chemotypes in unbiased library screens.
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29. 29
  Powers, R. A.; Morandi, F.; Shoichet, B. K. Structure-based discovery of a novel, noncovalent inhibitor of AmpC beta-lactamase Structure 2002, 10, 1013– 1023
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  29
  Structure-Based Discovery of a Novel, Noncovalent Inhibitor of AmpC β-Lactamase
  Powers, Rachel A.; Morandi, Federica; Shoichet, Brian K.
  Structure (Cambridge, MA, United States) (2002), 10 (7), 1013-1023CODEN: STRUE6; ISSN:0969-2126. (Cell Press)
  β-Lactamases are the most widespread resistance mechanisms to β-lactam antibiotics, and there is a pressing need for novel, non-β-lactam drugs. A database of over 200,000 compds. was docked to the active site of AmpC β-lactamase to identify potential inhibitors. Fifty-six compds. were tested, and three had Ki values of 650 μM or better. The best of these, 3-[(4-chloroanilino)sulfonyl]thiophene-2-carboxylic acid, was a competitive noncovalent inhibitor (Ki = 26 μM), which also reversed resistance to β-lactams in bacteria expressing AmpC. The structure of AmpC in complex with this compd. was detd. by x-ray crystallog. to 1.94 A and reveals that the inhibitor interacts with key active-site residues in sites targeted in the docking calcn. Indeed, the exptl. detd. conformation of the inhibitor closely resembles the prediction. The structure of the enzyme-inhibitor complex presents an opportunity to improve binding affinity in a novel series of inhibitors discovered by structure-based methods.
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30. 30
  Meng, E. C.; Shoichet, B. K.; Kuntz, I. D. Automated docking with grid-based energy evaluation J. Comput. Chem. 1992, 13, 505– 524
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  30
  Automated docking with grid-based energy evaluation
  Meng, Elaine C.; Shoichet, Brian K.; Kuntz, Irwin D.
  Journal of Computational Chemistry (1992), 13 (4), 505-24CODEN: JCCHDD; ISSN:0192-8651.
  The ability to generate feasible binding orientations of a small mol. within a site of known structure is important for ligand design. The authors present a method that combines a rapid, geometric docking algorithm with the evaluation of mol. mechanics interaction energies. The computational costs of evaluation are minimal because the authors precalc. the receptor-dependent terms in the potential function at points on a three-dimensional grid. In four test cases where the components of crystallog. detd. complexes are redocked, the "force field" score correctly identifies the family of orientations closest to the exptl. binding geometry. Scoring functions that consider only steric factors or only electrostatic factors are less successful. The force field function will play an important role in efforts to search databases for potential lead compds.
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31. 31
  Shoichet, B. K.; Leach, A. R.; Kuntz, I. D. Ligand solvation in molecular docking Proteins: Struct., Funct., Genet. 1999, 34, 4– 16
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32. 32
  Wei, B. Q. Q.; Baase, W. A.; Weaver, L. H.; Matthews, B. W.; Shoichet, B. K. A model binding site for testing scoring functions in molecular docking J. Mol. Biol. 2002, 322, 339– 355
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  A Model Binding Site for Testing Scoring Functions in Molecular Docking
  Wei, Binqing Q.; Baase, Walter A.; Weaver, Larry H.; Matthews, Brian W.; Shoichet, Brian K.
  Journal of Molecular Biology (2002), 322 (2), 339-355CODEN: JMOBAK; ISSN:0022-2836. (Elsevier Science Ltd.)
  Prediction of interaction energies between ligands and their receptors remains a major challenge for structure-based inhibitor discovery. Much effort has been devoted to developing scoring schemes that can successfully rank the affinities of a diverse set of possible ligands to a binding site for which the structure is known. To test these scoring functions, well-characterized exptl. systems can be very useful. Here, mutation-created binding sites in T4 lysozyme were used to investigate how the quality of at. charges and solvation energies affects mol. docking. At. charges and solvation energies were calcd. for 172,118 mols. in the Available Chems. Directory using a semi-empirical quantum mech. approach by the program AMSOL. The database was first screened against the apolar cavity site created by the mutation Leu99Ala (L99A). Compared to the electronegativity-based charges that are widely used, the new charges and desolvation energies improved ranking of known apolar ligands, and better distinguished them from more polar isosteres that are not obsd. to bind. To investigate whether the new charges had predictive value, the non-polar residue Met102, which forms part of the binding site, was changed to the polar residue glutamine. The structure of the resulting Leu99 Ala and Met102 Gln double mutant of T4 lysozyme (L99A/M102Q) was detd. and the docking calcn. was repeated for the new site. Seven representative polar mols. that preferentially docked to the polar vs. the apolar binding site were tested exptl. All seven bind to the polar cavity (L99A/M102Q) but do not detectably bind to the apolar cavity (L99A). Five ligand-bound structures of L99A/M102Q were detd. by X-ray crystallog. Docking predictions corresponded to the crystallog. results to within 0.4 A RMSD. Improved treatment of partial at. charges and desolvation energies in database docking appears feasible and leads to better distinction of true ligands. Simple model binding sites, such as L99A and its more polar variants, may find broad use in the development and testing of docking algorithms.
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33. 33
  Irwin, J. J.; Shoichet, B. K. ZINC—a free database of commercially available compounds for virtual screening J. Chem. Inf. Model. 2005, 45, 177– 182
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  ZINC - A Free Database of Commercially Available Compounds for Virtual Screening
  Irwin, John J.; Shoichet, Brian K.
  Journal of Chemical Information and Computer Sciences (2005), 45 (1), 177-182CODEN: JCISD8; ISSN:0095-2338. (American Chemical Society)
  A crit. barrier to entry into structure-based virtual screening is the lack of a suitable, easy to access database of purchasable compds. We have therefore prepd. a library of 727 842 mols., each with 3D structure, using catalogs of compds. from vendors (the size of this library continues to grow). The mols. have been assigned biol. relevant protonation states and are annotated with properties such as mol. wt., calcd. LogP, and no. of rotatable bonds. Each mol. in the library contains vendor and purchasing information and is ready for docking using a no. of popular docking programs. Within certain limits, the mols. are prepd. in multiple protonation states and multiple tautomeric forms. In one format, multiple conformations are available for the mols. This database is available for free download (http://zinc.docking.org) in several common file formats including SMILES, mol2, 3D SDF, and DOCK flexibase format. A Web-based query tool incorporating a mol. drawing interface enables the database to be searched and browsed and subsets to be created. Users can process their own mols. by uploading them to a server. Our hope is that this database will bring virtual screening libraries to a wide community of structural biologists and medicinal chemists.
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34. 34
  Bostrom, J.; Greenwood, J. R.; Gottfries, J. Assessing the performance of OMEGA with respect to retrieving bioactive conformations J. Mol. Graphics Modell. 2003, 21, 449– 462
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  34
  Assessing the performance of OMEGA with respect to retrieving bioactive conformations
  Bostrom, Jonas; Greenwood, Jeremy R.; Gottfries, Johan
  Journal of Molecular Graphics & Modelling (2003), 21 (5), 449-462CODEN: JMGMFI; ISSN:1093-3263. (Elsevier Science Inc.)
  OMEGA is a rule-based program which rapidly generates conformational ensembles of small mols. We have varied the parameters which control the nature of the ensembles generated by OMEGA in a statistical fashion (D-optimal) with the aim of increasing the probability of generating bioactive conformations. Thirty-six drug-like ligands from different ligand-protein complexes detd. by high-resoln. (≤ 2.0 Å) x-ray crystallog. have been analyzed. Statistically significant models (Q2 ≥ 0.75) confirm that one can increase the performance of OMEGA by modifying the parameters. Twenty-eight of the bioactive conformations were retrieved when using a low-energy cut-off (5 kcal/mol), a low RMSD value (0.6 Å) for duplicate removal, and a max. of 1000 output conformations. All of those that were not retrieved had eight or more rotatable bonds. The duplicate removal parameter was found to have the largest impact on retrieval of bioactive conformations, and the max. no. of conformations also affected the results considerably. The input conformation was found to influence the results largely because certain bond angles can prevent the bioactive conformation from being generated as a low-energy conformation. Pre-optimizing the input structures with MMFF94s improved the results significantly. We also investigated the performance of OMEGA in connection with database searching. The shape-matching program Rapid Overlay of Chem. Structures (ROCS) was used as search tool. Two multi-conformational databases were built from the MDDR database plus the 36 compds.; one large (max. 1000 conformations/mol) and one small (max. 100 conformations/mol). Both databases provided satisfactory results in terms of retrieval. ROCS was able to rank 35 out of 36 x-ray structures among the top 500 hits from the large database.
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35. 35
  Chambers, C. C.; Hawkins, G. D.; Cramer, C. J.; Truhlar, D. G. Model for aqueous solvation based on class IV atomic charges and first solvation shell effects J. Phys. Chem. 1996, 100, 16385– 16398
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  Model for Aqueous Solvation Based on Class IV Atomic Charges and First Solvation Shell Effects
  Chambers, Candee C.; Cramer, Christopher J.; Truhlar, Donald G.
  Journal of Physical Chemistry (1996), 100 (40), 16385-16398CODEN: JPCHAX; ISSN:0022-3654. (American Chemical Society)
  A new set of geometry-based functional forms is presented for parameterizing effective Coulomb radii and at. surface tensions of org. solutes in water. In particular, the radii and surface tensions depend in some cases on distances to nearby atoms. Combining the surface tensions with electrostatic effects included in a Fock operator by the generalized Born model enables one to calc. free energies of solvation, and exptl. free energies of solvation are used to parametrize the theory for water. At. charges are obtained by both the AM1-CM1A and PM3-CM1P class IV charge models, which yield similar results, and hence the same radii and surface tensions are used with both charge models. The authors considered 215 neutral solutes contg. H, C, N, O, F, S, Cl, Br, and I and encompassing a very wide variety of org. functional groups, and a mean unsigned error in the free energy of hydration of 0.50 kcal/mol using CM1A charges and 0.48 kcal/mol using CM1P charges was obtained. The predicted solvation energies for 12 cationic and 22 anionic solutes have mean unsigned deviations from expt. of 4.6 and 4.8 kcal/mol for models based on AM1 and PM3, resp.
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36. 36
  Li, J. B.; Zhu, T. H.; Cramer, C. J.; Truhlar, D. G. New class IV charge model for extracting accurate partial charges from wave functions J. Phys. Chem. A 1998, 102, 1820– 1831
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  New Class IV Charge Model for Extracting Accurate Partial Charges from Wave Functions
  Li, Jiabo; Zhu, Tianhai; Cramer, Christopher J.; Truhlar, Donald G.
  Journal of Physical Chemistry A (1998), 102 (10), 1820-1831CODEN: JPCAFH; ISSN:1089-5639. (American Chemical Society)
  We propose a new formalism, charge model 2 (CM2), to obtain accurate partial at. charges from a population anal. of wave functions by a parametrized mapping procedure, so that the resulting charges reproduce highly accurate charge-dependent observables. The new method, which produces class IV charges, is illustrated by developing CM2 mappings of Lowdin charges obtained from semiempirical and ab initio Hartree-Fock theory and d. functional theory, in particular AM1, PM3, HF/MIDI!, HF/6-31G*, HF/6-31+G*, BPW91/MIDI!, BPW91/6-31G*, B3LYP/MIDI!, and BPW91/DZVP calcns. The CM2 partial charges reproduce exptl. dipole moments with root-mean-square errors that are typically a factor of 7 better than dipole moments computed from Mulliken population anal., a factor of 3 better than dipole moments computed by Lowdin anal., and even a factor of 2 better than dipole moments computed from the continuous electron d. At the HF/6-31G* and B3LYP/MIDI! levels, the new charge model yields root-mean-square errors of 0.19 and 0.18 D, resp., for the dipole moments of a set of 211 polar mols. contg. a diverse range of structures and org. functional groups and the elements H, C, N, O, F, Si, P, S, Cl, Br, and I. A comparison shows that the new charge model predicts dipole moments more accurately than MP2/cc-pVDZ calcns., which are considerably more expensive. The quality of the results is similarly good for electrostatic potentials and for the other parametrizations as well.
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  An all-atom potential energy function for the simulation of proteins and nucleic acids is presented. This work is an extension of the CH united atom function recently presented by S. J. Weiner et al. (1984). The parameters of this function are based on calcns. on ethane, propane, n-butane, di-Me ether, Me Et ether, THF, imidazole, indole, deoxyadenosine, base-paired dinucleoside phosphates, adenine, guanine, uracil, cytosine, thymine, insulin, and myoglobin. These parameters were also used to carry out the 1st general vibrational anal. of all 5 nucleic acid bases with a mol. mechanics potential approach.
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  Nature Biotechnology (2007), 25 (2), 197-206CODEN: NABIF9; ISSN:1087-0156. (Nature Publishing Group)
  The identification of protein function based on biol. information is an area of intense research. Here the authors consider a complementary technique that quant. groups and relates proteins based on the chem. similarity of their ligands. The authors began with 65,000 ligands annotated into sets for hundreds of drug targets. The similarity score between each set was calcd. using ligand topol. A statistical model was developed to rank the significance of the resulting similarity scores, which are expressed as a min. spanning tree to map the sets together. Although these maps are connected solely by chem. similarity, biol. sensible clusters nevertheless emerged. Links among unexpected targets also emerged, among them that methadone, emetine and loperamide (Imodium) may antagonize muscarinic M3, α2 adrenergic and neurokinin NK2 receptors, resp. These predictions were subsequently confirmed exptl. Relating receptors by ligand chem. organizes biol. to reveal unexpected relationships that may be assayed using the ligands themselves.
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  Tondi, D.; Morandi, F.; Bonnet, R.; Costi, M. P.; Shoichet, B. K. Structure-based optimization of a non-beta-lactam lead results in inhibitors that do not up-regulate beta-lactamase expression in cell culture J. Am. Chem. Soc. 2005, 127, 4632– 4639
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  Structure-Based Optimization of a Non-β-lactam Lead Results in Inhibitors That Do Not Up-Regulate β-Lactamase Expression in Cell Culture
  Tondi, Donatella; Morandi, Federica; Bonnet, Richard; Costi, M. Paola; Shoichet, Brian K.
  Journal of the American Chemical Society (2005), 127 (13), 4632-4639CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)
  Bacterial expression of β-lactamases is the most widespread resistance mechanism to β-lactam antibiotics, such as penicillins and cephalosporins. There is a pressing need for novel, non-β-lactam inhibitors of these enzymes. One previously discovered novel inhibitor of the β-lactamase AmpC (I) has several favorable properties: it is chem. dissimilar to β-lactams and is a noncovalent, competitive inhibitor of the enzyme. However, at 26 μM its activity is modest. Using the x-ray structure of the AmpC/I complex as a template, 14 analogs were designed and synthesized. The most active of these, (II), had a Ki of 1 μM, 26-fold better than the lead. To understand the origins of this improved activity, the structures of AmpC in complex with compd. II and an analog were detd. by x-ray crystallog. to 1.97 and 1.96 Å, resp. II was active in cell culture, reversing resistance to the third generation cephalosporin ceftazidime in bacterial pathogens expressing AmpC. In contrast to β-lactam-based inhibitors clavulanate and cefoxitin, compd. II did not up-regulate β-lactamase expression in cell culture but simply inhibited the enzyme expressed by the resistant bacteria. Its escape from this resistance mechanism derives from its dissimilarity to β-lactam antibiotics.
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  [3H]CGS 21680, a selective A2 adenosine receptor agonist directly labels A2 receptors in rat brain
  Jarvis, Michael F.; Schulz, Rainer; Hutchison, Alan J.; Do, Un Hoi; Sills, Matthew A.; Williams, Michael
  Journal of Pharmacology and Experimental Therapeutics (1989), 251 (3), 888-93CODEN: JPETAB; ISSN:0022-3565.
  Characterization of the adenosine A2 receptor has been limited due to the lack of available ligands which have high affinity and selectivity for this adenosine receptor subtype. In the present study, the binding of a highly A2-selective agonist radioligand, [3H]CGS 21680 (I) is described. [3H]CGS 21680 specific binding to rat striatal membranes was saturable, reversible, and dependent on protein concn. Satn. studies revealed that [3H]CGS 21680 bound with high affinity (Kd =15.5 nM) and limited capacity (apparent Bmax = 375 fmol/mg protein) to a single class of recognition sites. Ests. of ligand affinity (16 nM) detd. from assocn. and dissocn. kinetic expts. were in close agreement with the results from the satn. studies. [3H]CGS 21680 binding was greatest in striatal membranes with negligible specific binding obtained in rat cortical membranes. Adenosine agonists ligands competed for the binding of 5 nM [3H]CGS 21680 to striatal membranes with the following order of activity; CGS 21680 = 5'-N-ethylcarboxamidoadenosine > 2-phenylaminoadenosine (CV-1808) ; 5'-N-methylcarboxamidoadenosine = 2-chloroadenosine > R-phenylisopropyladenosine > N6-cyclohexyladenosine > N6-cyclopentyltheophylline > S-phenylisopropyladenosine. The nonxanthine adenosine antagonist, CGS 15943A, was the most active compd. in inhibiting the binding of [3H]CGS 21680. Other adenosine antagonists inhibited binding in the following order; xanthine amine congener = (1,3-dipropyl-8-(2-amino-4-chloro)phenylxanthine > 1,3-dipropyl-8-cyclopentylxanthine > 1,3-diethyl-8-phenylxanthine > 8-phenyltheophylline > 8-cyclopentyltheophylline = xanthine carboxylic acid congener > 8-parasulfophenyltheophylline > theophylline > caffeine. The pharmacol. profile of both adenosine agonist and antagonist compds. to compete for the binding of [3H]CGS 21680 was consistent with a selective interaction at the high affinity adenosine A2 receptor. A high pos. correlation was obsd. between the pharmacol. profile of adenosine ligands to inhibit the binding of [3H]CGS 21680 and the selective binding of [3H]NECA (+50 nM CPA) to high affinity A2 receptors. However, some differences between these assays were found for compds. which have moderate affinity and nonselective actions at both the A1 and A2 adenosine receptor subtypes. Unlike data obtained with nonselective adenosine ligands, the present results indicate that [3H]CGS 21680 directly labels the high affinity A2 receptor in rat brain without the need to block binding activity at the A1 receptor. The high degree of selectivity (>170-fold) and high affinity of [3H]CGS 21680 make this the current ligand of choice for the in vitro characterization of high affinity A2 receptors.
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  2-Chloro-N6-[3H]cyclopentyladenosine ([3H]CPPA) - a high affinity agonist radioligand for A1 adenosine receptors
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  The tritiated analog of 2-chloro-N6-cyclopentyladenosine (CCPA) (I), an adenosine deriv. with subnanomolar affinity and a 10,000-fold selectivity for A1 adenosine receptors, has been examd. as a new agonist radioligand. [3H]CCPA was prepd. with a specific radioactivity of 1.58 TBq/mmol (43 Ci/mmol) and bound in a reversible manner to A1 receptors from rat brain membranes with a high affinity KD value of 0.2 nmol/L. In the presence of GTP, a KDvalue of 13 nmol/L was detd. for the low affinity state for agonist binding. Competition of several adenosine receptor agonists and antagonists for [3H]CCPA binding to rat brain membranes confirmed binding to an A1 receptor. Solubilized A1 receptors bound [3H]CCPA with similar affinity for the high affinity state. At solubilized receptors a reduced assocn. rate was obsd. in the presence of MgCl2, as has been shown for the agonist [3H]N6-phenylisopropyladenosine ([3H]PIA). [3H]CCPA was also used for detection of A1 receptors in rat cardiomyocyte membranes, a tissue with a very low receptor d. Kd-Value of 0.4 nmol-L and a Bmax-value of 16 fmol-platelet membranes, no specific binding of [3H]CCPA was measured at concns. up to 400 nmol/L, indicating that A2 receptors did not bind [3H]CCPA. Based on the subnanomolar affinity and the high selectivity for A1 receptors, [3H]CCPA proved to be a useful agonist radioligand for characterization of A1 adenosine receptors also in tissues with very low receptor d.
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  McGovern, Susan L.; Helfand, Brian T.; Feng, Brian; Shoichet, Brian K.
  Journal of Medicinal Chemistry (2003), 46 (20), 4265-4272CODEN: JMCMAR; ISSN:0022-2623. (American Chemical Society)
  Promiscuous small mols. plague screening libraries and hit lists. Previous work has found that several nonspecific compds. form submicrometer aggregates, and it has been suggested that this aggregate species is responsible for the inhibition of many different enzymes. It is not understood how aggregates inhibit their targets. To address this question, biophys., kinetic, and microscopy methods were used to study the interaction of promiscuous, aggregate-forming inhibitors with model proteins. By use of centrifugation and gel electrophoresis, aggregates and protein were found to directly interact. This is consistent with a subsequent observation from confocal fluorescence microscopy that aggregates conc. green fluorescent protein. β-Lactamase mutants with increased or decreased thermodn. stability relative to wild-type enzyme were equally inhibited by an aggregate-forming compd., suggesting that denaturation by unfolding was not the primary mechanism of interaction. Instead, visualization by electron microscopy revealed that enzyme assocs. with the surface of inhibitor aggregates. This assocn. could be reversed or prevented by the addn. of Triton X-100. These observations suggest that the aggregates formed by promiscuous compds. reversibly sequester enzyme, resulting in apparent inhibition. They also suggest a simple method to identify or reverse the action of aggregate-based inhibitors, which appear to be widespread.
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  Quantifying biogenic bias in screening libraries
  Hert, Jerome; Irwin, John J.; Laggner, Christian; Keiser, Michael J.; Shoichet, Brian K.
  Nature Chemical Biology (2009), 5 (7), 479-483CODEN: NCBABT; ISSN:1552-4450. (Nature Publishing Group)
  In lead discovery, libraries of 106 mols. are screened for biol. activity. Given the over 1060 drug-like mols. thought possible, such screens might never succeed. The fact that they do, even occasionally, implies a biased selection of library mols. We have developed a method to quantify the bias in screening libraries toward biogenic mols. With this approach, we consider what is missing from screening libraries and how they can be optimized.
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  Soelaiman, S.; Wei, B. Q.; Bergson, P.; Lee, Y. S.; Shen, Y.; Mrksich, M.; Shoichet, B. K.; Tang, W. J. Structure-based inhibitor discovery against adenylyl cyclase toxins from pathogenic bacteria that cause anthrax and whooping cough J. Biol. Chem. 2003, 278, 25990– 25997
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  Katritch, V.; Jaakola, V. P.; Lane, J. R.; Lin, J.; Ijzerman, A. P.; Yeager, M.; Kufareva, I.; Stevens, R. C.; Abagyan, R. Structure-based discovery of novel chemotypes for adenosine A(2A) receptor antagonists J. Med. Chem. 2010, 53, 1799– 1809
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  Structure-Based Discovery of Novel Chemotypes for Adenosine A2A Receptor Antagonists
  Katritch, Vsevolod; Jaakola, Veli-Pekka; Lane, J. Robert; Lin, Judy; IJzerman, Adriaan P.; Yeager, Mark; Kufareva, Irina; Stevens, Raymond C.; Abagyan, Ruben
  Journal of Medicinal Chemistry (2010), 53 (4), 1799-1809CODEN: JMCMAR; ISSN:0022-2623. (American Chemical Society)
  The recent progress in crystallog. of G-protein coupled receptors opens an unprecedented venue for structure-based GPCR drug discovery. To test efficiency of the structure-based approach, we performed mol. docking and virtual ligand screening (VLS) of more than 4 million com. available "drug-like" and "lead-like" compds. against the A2AAR 2.6 Å resoln. crystal structure. Out of 56 high ranking compds. tested in A2AAR binding assays, 23 showed affinities under 10 μM, 11 of those had sub-μM affinities and two compds. had affinities under 60 nM. The identified hits represent at least 9 different chem. scaffolds and are characterized by very high ligand efficiency (0.3-0.5 kcal/mol per heavy atom). Significant A2AAR antagonist activities were confirmed for 10 out of 13 ligands tested in functional assays. High success rate, novelty, and diversity of the chem. scaffolds and strong ligand efficiency of the A2AAR antagonists identified in this study suggest practical applicability of receptor-based VLS in GPCR drug discovery.
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Table S1 of structures of the 500 top-ranking molecules from the docking screen. This material is available free of charge via the Internet at http://pubs.acs.org.
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Structure-Based Discovery of A2A Adenosine Receptor Ligands

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Abstract

Introduction

Chart 1

Figure 1

Methods

Preparation of the Molecular Docking Screen

Similarity and Library Bias Calculations

A2A AR Receptor Binding and Functional Assay

Cell Culture and Membrane Preparation

Binding Assays

Cyclic AMP Accumulation Assay

Counterscreen for Colloidal Inhibition

Results and Discussion

Molecular Docking Screen and Compound Selection

Radioligand Displacement Assays and Docking Hit Rate

Figure 2

Predicted Binding Modes, Novelty, and Efficacy of the Discovered A2A AR Ligands

Figure 3

Is There Library Bias toward GPCR Chemotypes in Chemical Libraries?

Note Added after Initial Review of This Paper

Supporting Information

Terms & Conditions

Author Information

Acknowledgment

References

Cited By

Abstract

Chart 1

Figure 1

Figure 2

Figure 3

References

Supporting Information

Supporting Information

Terms & Conditions

STEP 1:

STEP 2:

Structure-Based Discovery of A_2A Adenosine Receptor Ligands

A_2A AR Receptor Binding and Functional Assay

Predicted Binding Modes, Novelty, and Efficacy of the Discovered A_2A AR Ligands